Charles Sturt University
Charles Sturt University

Associate Professor Manoranjan Paul

Associate Professor Manoranjan Paul

PhD Monash

Profile

Manoranjan Paul received the BSc Eng (honours) degree in Computer Science and Engineering from Bangladesh University of Engineering and Technology (BUET), Bangladesh, in 1997 and the PhD degree from Monash University, Australia in 2005. He has also completed Graduate Certificate in University Leadership in 2017 and Graduate Certificate in Learning & Teaching in Higher Education in 2015 from Charles Sturt University.

Currently, Manoranjan Paul is an Associate Professor in Computer Science and the Head of E-Health Research at Charles Sturt University (CSU).

Previously A/Prof Paul was an Assistant Professor/Lecturer (1997-01) at Ahsanullah University, Assistant Lecturer (2001-05) at Monash University, Post-Doctoral Research Fellow at University of New South Wales (2005-06), Post-Doctoral Research Fellow (2006-09) at Monash University, Post-Doctoral Research Fellow (2009-11) at Nanyang Technological University (Singapore), Lecturer (2011-12) at CSU, and Senior Lecturer (2013-16) at CSU. He was an Associate Director of Centre for Research in Complex Systems (2013-17).

His major research interests are in the fields:

  • Video Coding
  • Image Processing (medical imaging, hyperspectral)
  • E-Health
  • Human-Computer Interaction
  • EEG Signal Analysis
  • Cybersecurity
  • Computer Vision

He has published more than 150 fully refereed international journals, book chapters, books, and conference articles. A/Prof Paul regularly published in the top ranked journals such as IEEE Transactions. A/Prof Paul is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and Australian Computer Society (ACS).

A/Prof Paul is the ICT Researcher of the Year 2017 awarded by Australian Computer Society. He obtained Faculty Research Excellent Award 2013 and Faculty Research Supervision Excellence Award 2015 at CSU. He obtained $15 million competitive grant money including Australian Research Council (ARC) Discovery Project Grant, Australia-China Science Research Grant, Cybersecurity CRC, etc.

A/Prof Paul was an invited Keynote speakers in DICTA 2017, CSWN 2017, DICTA 2013, WoWMoM 2014, and ICCIT 2010. He is an Associate Editor of Eurasip Journal on Advances in Signal Processing (JCR Rank Q2). He is also a Guest Editor of Journal of Multimedia and Journal of Computers. He has supervised 12 PhD in completion. For detailed information, please visit his personal website.

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Teaching Responsibilities

  • ITC369: Computer Vision
  • ITC713: Advanced Readings in Information Technology
  • ITC200 Database Administration
  • ITC206 Programming in Java 1
  • ITC262 Operating Systems
  • ITC313 Programming in Java 2
  • ITC421 Programming in Java 1 for Postgraduate Students

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Grants

  • Manzur Murshed and Manoranjan Paul, "Multiview Video Coding using Cuboid Data Compression", Australian Research Council (ARC) Discovery Project, $315,000, 2013~2015 (External Grant).
  • L. Ang, K.P. Seng, Manoranjan Paul, and L. Zheng, "Spherical Digital Video Camera for High Precision and Rapid Imaging," CSU RIGB grant, 2015, $31,078.
  • Manoranjan Paul, Junbin Gao, Terry Bossomaier, and Michael Antolovich, "Hyperspectral imaging", Charles Sturt University RIGB grant, 2015, $63,110.
  • Manoranjan Paul and M Z. Parvez, "Epileptic seizure prediction", FoB Compact Funding, Charles Sturt University, 2015, $7,000.
  • Manoranjan Paul, "Video Workshop", FoB Compact Funding, Charles Sturt University, 2015, $10,000.
  • Subrata Chakraborty and Manoranjan Paul, "Depth and Texture Coding", Faculty of Business Compact Funding, 2014, $6,000.
  • Manoranjan Paul, "High performance computing", Execute Deans' Educational Equipment grant, 2014, $20,000.
  • Manoranjan Paul, Junbin Gao, Michael Antolovich, Terry Bossomaier, and Zahid Islam, "Depth image processing", Charles Sturt University Research Infrastructure Block Grants (RIBG), 2013, $50,000.
  • Michael Antolovich, Junbin Gao, Jim Tulip, Manoranjan Paul, David Tien, Wayne Moore, Kevin Wilkins, and David Tilbrook (2013), "Imaging Under Dangerous Conditions, specifically within the Mining Industry," Faculty Compact Funding, 2013, $85,000.
  • Manoranjan Paul, Junbin Gao, Michael Antolovich, Terry Bossomaier, and Zahid Islam, "Abnormal event detection", Charles Sturt University Research Infrastructure Block Grants (RIBG), 2012, $43,000.
  • Junbin Gao, Terry Bossomaier, Manoranjan Paul, Michael Antolovich, and Paul Kwan, "WAREIGS: Wavelet-Network-Based Augmented-Reality-Enhanced Image-Guided Surgery," Australia-China Science Research Fund (ACSRF), 2012, $38,000(External Grant).
  • Junbin Gao, Michael Antolovich, Manoranjan Paul, and Jim Tulip, "Efficient Algorithms for Nuclear Norm Minimization," Faculty of Business Compact grant, 2012-2013, $12,702.
  • Manoranjan Paul, Junbin Gao, Michael Antolovich, and Jim Tulip, "Eye controlled video coding," Faculty of Business Compact grant, 2012-2013, $12,929.
  • Manoranjan Paul, Junbin Gao, Michael, and Terry Bossomaier, "Mentoring support for obtaining grant," Faculty of Business Compact grant, 2011, $9,902.
  • Manoranjan Paul, Junbin Gao, Michael, and Terry Bossomaier, "Project Funding," Faculty of Business Compact grant, 2011, $4,600.
  • Junbin Gao, Michael Antolovich, Manoranjan Paul, Jim Tulip and David Tien, "Visiting Fellow," Faculty of Business Compact grant, 2011, $14,036.
  • Manoranjan Paul, "Charles Sturt University Seed Grant 2011", 2011, $4,620.
  • Manoranjan Paul, "A Real-Time Human Behaviour Recognition Framework for Video Surveillance," Faculty of Information Technology, Monash University Early Career Grant, 2008, $20,000 (Top ranked project but could not obtained due to CI's institution move).
  • Manoranjan Paul and Weisi Lin, "Undergraduate Research Experience on Campus (URECA) project," Nanyang Technological University, 2009, 4× $3600 = $14,400.
  • Weisi Lin and Manoranjan Paul, "Undergraduate Research Experience on Campus (URECA) project," Nanyang Technological University, 2010, 2× $3600 = $7,200.
  • Manoranjan Paul, Manzur Murshed, and Xiaofang Zhou, "Video Signal Processing and Communication Taskforce Grant," ARC (Australian Research Council) Research Network in Enterprise Information Infrastructure (EII), 2007, $25,000 (External Grant).
  • Manoranjan Paul and Heng Tao, "First Australian Video Conference (AusVideo) Grant," ARC (Australian Research Council) Research Network in Enterprise Information Infrastructure (EII), 2007, $10,000 (External Grant).
  • Manoranjan Paul, "EII workshop Travel Grant," (Australian Research Council) Research Network in Enterprise Information Infrastructure (EII), 2006-08, $6,000 (External Grant).
  • Manoranjan Paul, "Gippsland Linkage and Discovery Initiative Scheme", Monash University, 2008, $5,000.
  • Manoranjan Paul, "Publication Time Release Scheme (PTRS)," Monash University, Gippsland Campus, 2008, $2,500.
  • Manoranjan Paul, "National & International Conference Travel Grant Scheme (NICTGS)," Monash University, Gippsland Campus, 2008, $2,000.
  • Manoranjan Paul, "National Conference Travel Grant Scheme," Monash University, Clayton Campus, 2008, $700.
  • Manoranjan Paul, "Higher Study Grants," Ahsanullah University of Science and Technology, 2001, $7500.

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Research Focus

Project 1: EEG Signal Analysis

Researchers: A/Prof Manoranjan Paul (CSU), Dr. Michael Antolovich (CSU), and Dr. Zavid Parvez (ISI Foundation, Italy and A/Prof Paul’s previous PhD student at CSU)

An Electroencephalogram (EEG) is a non-invasive graphical record of ongoing electrical activity captured from the scalp which is produced by firing of neurons of the human brain due to internal and/or external stimuli. It has great potential for the diagnosis to treatment of mental disorder and brain diseases. We are focusing on detecting and predicting of epileptic seizure period by analysis EEG signals. We are looking for other applications of EEG signals.

Outcome: We are able to predict epileptic seizure by 15 minutes earlier with 90% accuracy when we use invasive EEG signals. I successfully supervised a PhD project. We published 14 papers in this area including two journals in IEEE Transactions on Biomedical Engineering and IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Left image: Multi-view video coding: Disparity-adjusted 3D block formation Right Image: Pattern-based video coding: Background-foreground separation using binary pattern mask.

Project 2: Video Coding and Compression

Researchers: A/Prof Manoranjan Paul (CSU), Professor Manzur Murshed (FedUni), A/Professor Weisi Lin (NTU), Dr. Mortuza Ali (FedUni), Dr. Tanmoy Debnath (CSU), Dr. Subrata Chakraborty (USQ), Shampa Shahriyar (PhD student, Monash University), Pallab Podder (PhD student, CSU) and Niras C.V. (PhD student, Macquarie University)

Video conferencing, video telephony, tele-teaching, tele-medicine and monitoring systems are some of the video coding/compression applications that have attracted considerable interest in recent years as 3D video is now reality. The burgeoning Internet has increased the need for transmitting (non-real-time) and/or streaming (real-time) video over a wide variety of different transmission channels connecting devices of varying storage and processing capacity. Stored movies or animations can now be downloaded and many reality-type interactive applications are also available via web-cams. In order to cater for devices with different storage and transmission bandwidth requirements, raw digital video data need to be coded at different bit rates with different timing complexity. Sometimes for realistic views of the scene of action, we also need to encode/ compress/ process videos with multiple cameras (multi-view) from different angles. We are focusing on video coding and compression in different scales suitable for different devices with accepted quality and computational time.

Outcome: An ARC DP13 which partially solve interactive problem for 3D video call. Our contributions have been adapted in the latest video coding standards e.g. HEVC, VP9, AVS. Published 4 IEEE Transactions. Supervising three PhD projects on it.

Object Detection from PETS2006 sequence

Project 3: Object Detection and Background Modeling

Researchers: A/Prof Manoranjan Paul (CSU), Professor Manzur Murshed (FedUni), A/Professor Weisi Lin (NTU), and Dr. Subrata Chakraborty (USQ)

Object detection from the complex and dynamically changing background is still a challenging task in the field of computer vision. Adaptive background modeling based object detection techniques are widely used in machine vision applications for handling the challenges of real-world multimodal background. But they are constrained to specific environment due to relying on environment specific parameters, and their performances also fluctuate across different operating speeds. Camera motions of a scene makes dynamic background modeling more complicated. We are focusing on dynamic background modeling in challenging environments and their applications in different fields.

Outcome: We are able to extract background from a challenging environment. We have successfully applied background modeling in video coding and video summarization. Published 2 IEEE Transactions. Supervised one PhD project to completion.

Eye tracker and heat map

Project 4: Eye tracking Technology

Researchers: A/Prof Manoranjan Paul (CSU), Dr. Tanmoy Debnath (CSU), and Pallab Podder (PhD student, CSU)

An eye tracker is a device to capture eye movement and its duration. In my lab, we have an eye tracker. We are focusing on various research issues e.g., Abnormal event detection and prediction, speech/alcohol/drug impairment detection, retail/advertising effectiveness, video communication for deaf people, eye can be used as an input device, improving electronic document design, increasing user acceptability of learning technologies, telemedicine, and remote surgery.

Outcome: We are able to determine human engagement using eye tracker. We are able to find some facts of marker discrepancy in multiple markers scenarios. We are also able to assess quality of a video when there is no reference. We have published three papers in this area.

Project 5: Hyperspectral Imaging

Researchers: A/Prof Manoranjan Paul (CSU), Professor Junbin Gao (University of Sydney), Professor Terry Bossomaier (CSU), and Rui Xiao (PhD student, CSU)

Hyperspectral imaging sensor divides images into many bands which can be extended beyond visible. The applications of hyperspectral imaging are in the fields of military to detect chemical weapon, geological survey, agriculture to quantify crops, mineralogy to identify different minerals, physics to identify different properties of materials, surveillance to detect different objects and reflections, measurement of surface CO2 emissions, mapping hydrological formations, tracking pollution levels, and more. We are investigating different applications of hyperspectral imaging for example Fruit-life span prediction.

Outcome: We are able to model a spectral predictor and develop a context-adaptive entropy coding technique which give us up to 7 compression ratio in some images whereas the current state-of-the-art methods only can provide around 3 compression ratio.  We published 4 papers in area including PLoS ONE 2016 journal.

Project 6: Video Summarising

Researchers: A/Prof Manoranjan Paul (CSU) and MD Salehin (PhD student, CSU)

In our daily life we capture video for various purposes such as security, entertainment, monitoring, investigating and so on. It requires huge memory space to store as well as enormous time to retrieve or replay important information manually from this high volume of videos. In this project, we explore the various features based on scene content, scene transition, human visual systems to extract important importation for particular application and make a shorter version of the video.

Outcome: We are able to summarize different type videos including surveillance, sports, movie, etc. We published 10 papers in this area including PLOS ONE 2017, JOSA A 2017.

Project 7: Collagen Defect Detection

Researchers: A/Prof Manoranjan Paul (CSU) and Chris Williams (Honors student, CSU)

Machine vision is now being extensively used for defect detection in the manufacturing process of collagen-based products such as sausage skins which is a multimillion dollar industry worldwide. At present the industry standard is to use a LabView software environment, whereby a graphical interface is used to manage and detect any defects in the collagen skins. Available data corroborates that this method allows for false positives to appear in the results where creases or folds are resolved to be defects in the product instead of being a by-product in the inspection process. This is directly responsible for reducing the overall system performance and resulting wastage of resources. Hence novel criteria were added to enhance the current techniques used with defect detection as elaborated in this paper. The proposed improvements aim to achieve a higher accuracy in detecting both true and false positives by utilizing a function that probes for the color deviation and fluctuation in the collagen skins. From the operating point of view, this method has a more flexible approach with a higher accuracy than the original graphical LabView program and could be incorporated into any programming environment. After implementation of the method in a well-known Australian company, investigational results demonstrate an average 26% increase in the ability to detect false positives with a corresponding substantial reduction in operating cost.

Project 8: View Synthesis for 3D video and Free Viewpoint Video

In recent years, free viewpoint video (FVV) or Free Viewpoint Television (FVT) technology is increasing popularity for rendering intermediate views from existing adjacent views to avoid the large volume of video data transmission. For generating an intermediate view on a remote display, Depth Image Based Rendering (DIBR) techniques are normally used, however, sometimes it has some missing pixels due to inaccurate depth, low precision rounding error and occlusion problem. To address the issue, we are working on hole filling technique, view rendering, and depth coding, 3D video formation.

Outcome: I can reconstruct a better virtual view compared to the existing one. I have published 12 papers on this area including IEEE Transactions on Image Processing (Rank 1 in Signal Processing, CORE A*).

Project 9: Medical Imaging

  • Diabetic retinopathy: Retinal vessel segmentation plays a key role in the detection of numerous eye diseases, and its reliable computerized implementation becomes important for automatic retinal disease screening systems. A large number of retinal vessel segmentation algorithms have been reported, primarily based on three main steps including uniforming background uniform, using the second-order Gaussian detector and applying binarisation. These methods though improve the accuracy levels, their sensitivity to low-contrast in vessels still needs attention. We are conducting research to improve retinal vessel extraction. This research is suitable for retinal image computer analyses such as automated screening for early diabetic retinopathy detection.
  • Augmented reality for surgery: We are trying to improve geometric accuracy for Augmented Reality (AR) in Oral and Maxillofacial Surgeries. We have some success on it and submitted a paper on it.
  • Bone cancer detection: We have used bioinformatics to detect bone cancer. We have published a paper on it in Journal of Computers, 2017.
  • Breast Implant: We are conducting research on visualising the Blood Vessels in Breast Implant Surgeries for better accuracy in augmented reality. We have some success and submitted a paper on it.
  • Fall detection:  With the help of ICT, we have developed a fall detection system using depth camera information. We have submitted a paper on it.

Outcome: Our unsupervised vessel extraction method for detecting vessel provides comparable results compared to the popular supervised methods. I have published 5 papers on this area including journals in Signal, Image and Video Processing 2017 and Pattern Analysis and Application 2017.

Retinal scan images - described below
Analysis of output images:
(a) ground truth (right eye image), (b) output image (right eye image),
(c) ground truth (left eye image), and (d) Output image (left eye image).

Falling from a chair

Falling towards camera

 
Falling sideways

Picking up object

Sitting on sofa

Sweeping floor

Fall Detection: Some challenging scenario where the existing method fails as it considers as fall for sweeping floor, picking object but the proposed method is successful.

Upper front teeth image registration

Lower front when patient moves

Image overlaying if patient moves

If surgical instrument moves

When surgical instrument moves

Mandibular reconstruction

If surgical instrument moves

Image overlaying if patient moves

AR on Oral and Maxillofacial Surgeries and AR for Visualising the Blood Vessels in Breast Implant Surgeries

Project 10: Early Diagnosis of Alzheimer’s Disease

Successful, timely diagnosis of neuropsychiatric diseases is key to management. Research efforts in the area of diagnosis of Alzheimer’s disease have used various aspects of computer-aided multi-class diagnosis approaches with varied degrees of success. However, there is still need for more efficient and reliable approaches to successful diagnosis of the disease. We are conducting research to diagnose the Alzheimer’s disease so that we are able to detect problem earlier.

Outcome: We use k-sparse autoencoder method with deep learning framework for this purpose. The results show promising results. I am supervising a Professional Doctorate project on it. I have published 1 paper on this area.

Project 11: Cardiopulmonary measurement using the smartphone

The aim of the project is to develop a non-contact cardiopulmonary detection method in natural disaster rescue relief, based on the use of frequencies and antennas that are similar to current smartphone-like devices. Current focuses are in particular on the current Wi-Fi 2.4 GHz and 5 GHz radio frequencies wavelength, Doppler effect radar, signal processes, and a signal noise cleansing technique that detects and measures vital signs. This approach could be used as an alternative to the commercially designed, devices currently used for heartbeat and respiration detection during rescue relief with the aim of reducing device transit time and cost. This project further evaluates a new type of multi-directional antenna that could be used to detect the human physiology pulsatile from 360o degree view.

Outcome: I am supervising a DIT project on it.

Detection theory of heart and breathing using continued wave

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Professional Activities

Associate Director (2013-2017), Centre for Research in Complex Systems (CRiCS)

Head, E-Health Research Group, CSU.

ARC (Australian Research Council) Assessor Since 2013:

  • ARC Discovery Project
  • ARC Future Fellowship

Current PhD Supervision

  • Shampa Shahriar, “3D Video coding,” Monash University.
  • Bin Liang, “Human Gesture Detection”, CSU.
  • M. Zavid Parvez, “Detection and Prediction of Epileptic Seizure using EEG signal Analysis”, CSU. (Completed)
  • Rui Xiao, “Hyperspectral imaging,” CSU.
  • Pallab Podder, “Efficient video coding”, CSU.
  • Motiur Rahman, View synthesis, CSU.
  • MD. Salehin, Video summarization, CSU.
  • Niras C. V., Motion estimation hardware design, Macquarie University
  • Toufique Soomro, Retinal Vessel, CSU

Editorial (from 2009)

  • M. Aziz, M. S. Alam, V. K. Asari, M. Paul, M. Rahman, S. Zhang, and M. A. Rahman (2014): Editorial. Special issue on the selected papers from IEEE International Conference on Computer & IT (IEEE ICCIT-12), Journal of Computers, 9(8), 1739-1742, SJR Rank Q3.
  • M. Murshed, M. Paul, S. Zhang, M. A. Karim (2012): Editorial. Special issue on the selected papers from IEEE ICCIT-11, Journal of Multimedia, 7(5), 325-326, SJR Rank Q2.
  • M. Murshed, M. Paul, S. Zhang, M. A. Karim (2011): Editorial. Special issue on the selected papers from IEEE ICCIT-10, Journal of Multimedia, 6(5), 393-394, SJR Rank Q2.
  • M. Murshed, M. Paul, S. Zhang, M. A. Karim (2010): Editorial. Special issue on the selected papers from IEEE ICCIT-09, Journal of Multimedia, 5(6), 541-542, SJR Rank Q2.
  • M. A. Karim, M. Murshed, M. Paul, S. Zhang (2010): Editorial. Special issue on the selected papers from IEEE ICCIT-08, Journal of Multimedia, 5(1), 1-2, SJR Rank Q2.

Journal Editor:

Keynote Speaker

Session Chair/PC member:

  • Conference Chair:
    • General Co-Chair: Pacific-Rim Symposium on Image and Video Technology (PSIVT) 2019
    • Program Co-Chair: IEEE Int. Conference on Digital Image Computing: Techniques and Applications (DICTA) 2018
    • Program Co-Chair: Pacific-Rim Symposium on Image and Video Technology (PSIVT) 2017
    • General Chair: E-Health Workshop on Remote Health using Technology (RHT) 2017
    • Publicity Chair: IEEE Int. Conference on Digital Image Computing: Techniques and Applications (DICTA) 2016
    • General Chair: Australian Workshop on Video/Image Coding, Processing, and Understanding (VICPU) 2015
    • General Co-Chair: “Video Everywhere” Workshop in IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2014
    • General Co-Chair: “Free viewpoint video understanding and challenges” Workshop in IEEE Picture Coding Symposium (PCS) 2015
    • General Co-Chair: “New Video Coding Technologies” workshop in IEEE International Symposium on Circuits and Systems (ISCAS) 2010
    • General Chair: Early Career Researcher (ECR) workshop, 2008
    • General Chair: Video signal processing and communication workshop, 2007
    • General Chair: Video/image processing 2006, Monash University
  • Session Chair:
    • IEEE PSIVT 2017
    • IEEE ICASSP 2015
    • IEEE ICME 2014
    • IEEE ISCAS 2010
    • IEEE ICCIT 2010
    • IEEE ICIS 2007

International Journal Reviewer

  • IEEE Transactions on Image Processing
  • IEEE Transactions on Circuits and Systems for Video Technology
  • IEEE Transactions on Multimedia
  • IEEE Transactions on Circuits and Systems Part 1
  • IEEE Communication Letter
  • IEEE Signal Processing Letter
  • International Journal of Visual Communication and Image Representation
  • IET Image Processing
  • ACM Transactions on Multimedia Computing, Communications, and Applications

Membership

  • IEEE (Senior Member)
  • IEEE Signal Processing Society (Senior Member)
  • IEEE Communication Society (Senior Member)
  • Australian Computer Society (ACS) (Senior Member)
  • Australian Research Council Network in Enterprise Information Infrastructure (EII)

Seminar presentation at different International Conferences such as

  • PSIVT 2017 (Wuhan, China)
  • ICME 2017 (Hong Kong)
  • DICTA 2017 (Sydney, Australia)
  • DICTA 2016 (Gold Coast Australia)
  • LICE 2016, 2016 (London, UK)
  • IEEE ICVNZ 2015 (Auckland, New Zealand)
  • PSIVT 2015 (Auckland, New Zealand)
  • IEEE ICASSP 2015 (Brisbane, Australia)
  • IEEE MMM 2015
  • IEEE ICME 2014
  • IEEE ICCIT 2014
  • IEEE ICECE 2014
  • IEEE WoWMoM Video Everywhere workshop (Keynote speaker)
  • DICTA-2014
  • DICTA 2013, Australia (Tutorial Speaker)
  • IEEE ICIP-2013, Australia
  • IEEE ICCIT 2012, Bangladesh
  • IEEE ICASSP-2012, Japan
  • IEEE DICTA 2011, Australia
  • IEEE ICCIT-2010 (Keynote Speaker and Session Chair), Bangladesh
  • IEEE ICIP-2010, Hong Kong
  • IEEE ISCAS-2010 (Session Chair and Special Session Organizer), France
  • IEEE ICIP-2008, USA
  • IEEE MMSP-2008, Australia
  • IEEE ICIS-2007 (Session Chair), Australia
  • ICCIT-2006, Bangladesh
  • MMM-2007, Singapore
  • IEEE ICASSP-2004, USA
  • IEEE ICME-2004, USA
  • Post IT-2004, Australia
  • ICAPR -2003, India
  • IEEE ICCIT-2003, Bangladesh

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Publications

The detailed publication list with preprint copy is available at http://csusap.csu.edu.au/~rpaul/.

PhD Thesis:

  • M. Paul, "Block-based very low bit rate video coding using pattern templates" PhD thesis in fulfilment of the requirements for the degree of Doctor of Philosophy, Monash University, 2005.

Book (from 2009):

  • M. Paul (2017), “Vision-aided 2D and 3D Video Coding,” Wiley’.
  • M. Paul and M. Murshed (2014), “Very low bit rate video coding,” Scholars’ Press, ISBN: 978-3-639-66780-6.

Book Chapter:

  • Parvez, Z. M. and Paul, M. (2015), “Prediction and Detection of Epileptic Seizure by Analysing EEG Signals,” for the upcoming book “Biomedical Image Analysis and Mining Techniques for Improved Health Outcomes,” edited by Nilanjan Dey, publisher: IGI-Global, 2015.
  • M. Paul, and W. Lin (2013), “Computer Vision-Aided Video Coding,” a book chapter on “Advanced Video Communications over Wireless Networks ,” edited by Ce Zhu and Yuenan Li, publisher: CRC PRESS of the Taylor and Francis Group, LLC, pp. 57-84, January 7, 2013, ISBN-10: 1439879982, ISBN-13: 978-1439879986.
  • M. Paul, and M. Murshed (2008), “Pattern based video coding,” a book chapter for the book “Handbook of Research on Modern Systems Analysis and Design Technologies and Applications”, edited by Mahbubur Rahman Syed and Sharifun Nessa Syed, Minnesota State University, Mankato, USA, published by Idea Group, pp. 469 – 483,  2008.
  • M. Paul, M. Murshed, and L. Dooley (2005), “Very low bit-rate video coding,” a book chapter for the book “Video Data Management and Information Retrieval”, edited by Sagarmay Deb. Idea Group Inc. USA, Chapter 5, pp. 100-147, 2005.

Journal Publications:

  • Paul, M. (2017) “Efficient Multiview Video Coding using 3D Coding and Saliency-based Bit Allocation,” IEEE Transactions on Broadcasting, [CORE A and JCR Q1].
  • Rahaman, DM M. and Paul, M. (2017) “Virtual View Synthesize for Free Viewpoint Video and Multiview Video Compression using Gaussian Mixture Modelling,” IEEE Transactions on Image Processing, [CORE A* and Rank 1 in Signal Processing].
  • Parvez, M. Z., and Paul, M. (2017) “Seizure Prediction using Undulated Global and Local Features,” IEEE Transactions on Biomedical Engineering, 64(1), pp. 208-17. [CORE A* and JCR Q1].
  • Vayalil, N. C., Paul, M., and Kong, Y.  (2017) “A Residue Number System Hardware Design of Fast-Search Variable-Motion-Estimation Accelerator for HEVC/H.265,” IEEE Transactions on Circuits and Systems for Video Technology, [Rank 1 in Multimedia and JCR Q1].
  • Salehin MM, Paul, M, Kabir MA (2017), “Video summarization using line segments, angles and conic parts,” PLoS ONE 12(11) [CORE A and JCR Q1]
  • Chakraborty, S., Paul, M. Murshed, M. and Ali, M. (2017), “Adaptive weighted non-parametric background model for efficient video coding,” Neurocomputing, Vol. 226, pp. 35-45. [JCR Q1]
  • Salehin, MD. and Paul, M.. (2017), “Adaptive Fusion of Human Visual Sensitive Features for Surveillance Video Summarization,” Journal of the Optical Society of America. A, Optics and Image Science and Vision. 34(5), pp. 814-826. [SJR[1] Q1]
  • Dusselaar, R. and Paul, M. (2017), “Hyperspectral image compression approaches: opportunities, challenges and future directions: discussion,” Journal of the Optical Society of America. A, Optics and Image Science and Vision. Vol 34. No. 12, pp. 2170-2180, [SJR Q1]
  • Halder, K. K., Paul, M., Tahtali, M., Anavati, S. G., and Murshed, M. (2017), “Correction of geometrically distorted underwater images using shift map analysis,” Journal of the Optical Society of America. A, Optics and Image Science and Vision, vol. 34, no. 4, pp. 666-673. [SJR Q1]
  • Soomro, T.,  Khan, M.A.U., Gao, J., Khan, T. M., and Paul, M. (2017), “Impact of Image Contrast Normalisation on Segmentation Model: A Retinal Image Case,” Journal of Signal, Image and Video Processing, [SJR Q2]
  • Podder, P., Paul M., DM, M. Rahaman, and Murshed, M. (2017), “Improved Depth Coding for HEVC Focusing on Depth Edge Approximation,” Signal Processing: Image Communication, vol. 55, pp. 80-92. [GCM Rank 8 in Multimedia, JCR Q2]
  • Soomro, T., Gao, J. Khan, T., Hani, A. F. M., Khan, M. A. U, and Paul, M. (2017), “Computerised approaches for the detection of diabetic retinopathy using retinal fundus images: a survey,” Pattern Analysis and Applications, https://doi.org/10.1007/s10044-017-0630-y. [SJR Q2]
  • Murugesan, Y. P., Prasad, P.W.C., Alsadoon, A., and Paul, M. (2017), “A Novel Rotational Matrix and Translation Vector (RMaTV) algorithms:  Geometric Accuracy for Augmented Reality (AR) in Oral and Maxillofacial Surgeries,” International Journal of Medical Robotics and Computer Assisted Surgery, SNIP 0.794, Impact factor 1.6, [CORE B].
  • Vallaboju, S., Prasad, P.W.C., Alsadoon, A., and Paul, M. (2017), “Bioinformatics Image based Decision Support System for Bone Cancer Detection,” Journal of Computers, SNIP 0.379, Accepted in 26th August 2017, [SCR Q3].
  • P. Podder, M. Paul and M. Murshed (2017), “A Novel No-reference Subjective Quality Metric for Free Viewpoint Video Using Human Eye Movement,” Springer Lecture Notes in Computer Science (LNC), (PSIVT 2017 CORE B), SJR Q2.
  • X. Rui and M. Paul (2017), “Hybrid adaptive prediction mechanisms with multilayer propagation neural network for hyperspectral image compression,” Springer Lecture Notes in Computer Science (LNC), (PSIVT 2017 CORE B), SJR Q2.
  • Parvez, M. Z. and Paul, M. (2016), “Epileptic Seizure Prediction by Exploiting Spatiotemporal Relationship of EEG Signals using Phase Correlation,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(1):158-68. [CORE A* and JCR Q1].
  • Paul, M., Xiao, R., Gao, J. and Bossomaier, T. (2016), “Reflectance prediction modelling for residual-based hyperspectral image coding,” PLoS ONE, 2016. [CORE A].
  • Podder, P., Paul, M. and Murshed, M. (2016), “Fast Mode Decision in HEVC by Exploiting Dominated Motion and Saliency Features,” PLoS ONE, 2016. [CORE A].
  • Podder, P., Paul, M., and Murshed, M. (2016), “A Novel Motion Classification Based Intermode Selection Strategy for HEVC Performance Improvement,” Neurocomputing, Vol 173, pp. 1211-1220. [JCR Q1]
  • Paul, M. (2016), “Efficient Multi-view Video Coding using 3D Motion Estimation and Virtual Frame,” Neurocomputing, Vol. 175, pp. 544-554. [JCR Q1]
  • Ali, M., Murshed, M., Shahriyar, S and Paul, M. (2016), Lossless image coding using hierarchical decomposition and recursive partitioning,” APSIPA Transactions on Signal and Information Processing, [In 2013 SJR Q1]
  • Parvez, M. Z. and Paul, M. (2015), “Epileptic seizure detection by exploiting temporal correlation of electroencephalogram signals,” IET Signal Processing, 9(6), pp. 467-475. [SJR Q2]
  • Xiao, R. and Paul, M. (2015), “Efficient Compression of Hyperspectral Images Using Optimal Compression Cube and Image Plane,” Springer Lecture Notes in Computer Science (LNC), vol. 8935, 167-79. [SJR Q2]
  • Salehin, MD., Paul, M. (2015), “ Fusion of Foreground Object, Spatial and Frequency Domain Motion Information for Video Summarization,” Springer LNC, vol. 9555: 319-331. [SJR Q2]
  • Williams, C. D., Paul, M., and Debnath, T. (2015), “Enhancing Automated Defect Detection in Collagen Based Manufacturing by Employing a Smart Machine Vision,” Springer LNC, Vol. 9555:55-66. [SJR Q2]
  • Podder, P., Paul, M. and Murshed, M. (2015), “Fast Coding Strategy for HEVC by Motion Features and Saliency Applied on Difference between Successive Image Blocks,” Springer LNC, 9431:175-86. [SJR Q2]
  • Parvez, M. Z. and Paul, M. (2014), “Epileptic Seizure Detection by Analyzing EEG Signals using Different Transformation Techniques,” Neurocomputing, vol. 145, pp. 190-200. [JCR Q1]
  • Parvez, M. Z. and Paul, M., and Antolovich, M. (2014), “Detection of Pre-stage of Epileptic Seizure by Exploiting Temporal Correlation of Decomposed EEG Signals,” Medical and Bioengineering, 4(2), 110-16.
  • Paul, M., Lin, W., Lau, C. T., and Lee, B. –S. (2014), “A Long Term Reference Frame for Hierarchical B-Picture based Video Coding,” IEEE Transactions on Circuits and Systems for Video Technology, 20(10), 1729-42. [Rank 1 in Multimedia, JCR Q1].
  • Parvez, M. Z. and Paul, M. (2014), “Novel approaches of EEG signal classification using IMF bandwidth and DCT frequency,” Biomedical Engineering: Applications, Basis and Communications, 27(3) [SJR Q4].
  • Paul, M., Lin, W., Lau, C. T., and Lee, B. –S. (2013), "Video Coding Using Background Modelling," EURASIP Journal on Advances in Signal Processing, [JCR Q2]
  • Paul, M., Haque, S., and Chakraborty, S. (2013), “Human detection in surveillance videos and its applications - A review,” EURASIP J. Advances in Signal Processing, 2013:176.[JCR Q2]
  • Paul, M., Lin, W., Lau, C. T., and Lee, B. –S. (2013), “Pattern-based video coding with dynamic background modelling," EURASIP J. Advances in Signal Processing, 2013-138. [JCR Q2]
  • Paul, M. (2012), "Efficient Video Coding using Optimal Compression Plane and Background Modelling," IET Image Processing, 6(9): 1311-18. [GCM Rank 13 in Multimedia, SJR Q2]
  • M. Paul and Manzur Murshed (2012), "Efficient Pattern Index Coding Using Syndrome Coding and Side Information," Int. Journal of Engineering and Industries, vol. 3, no. 3, pp. 1-12, 2012. ISSN: 2093-5765.
  • Paul, M., Lin, W., Lau, C. T., and Lee, B. –S. (2011), “Direct Intermode Selection for H.264 Video Coding using Phase Correlation,” IEEE Transactions on Image Processing, 20(2): 461-71. [CORE A*].
  • Liu, A., Lin, W., Paul, M., and Zhang, F. (2011), “Optimal Compression Plane Determination for Video Coding,” IEEE Transactions on Image Processing, 20(10), pp. 2788-2799. [CORE A*].
  • Paul, M., Lin, W., Lau, C. T., and Lee, B. –S. (2011), “Explore and model better I-frame for video coding,” IEEE Transactions on Circuits and Systems for Video Tech., 21(9):1242-54. [Rank 1 in Multimedia, JCR Q1].
  • Paul, M. and Murshed, M. (2011), “Video Coding Using Arbitrarily Shaped Block Partitions in Globally Optimal Perspective," EURASIP J. on Advances in Signal Processing, 2011-16. [JCR Q2]
  • Paul, M., Murshed, M. (2010), “Video coding focusing on block partitioning and occlusion,” IEEE Transactions on Image Processing, 19(3): 691-701. [CORE A*]
  • Liu, A., Lin, W., Paul, M., and Zhang, F. (2010), “Just Noticeable Difference for Image Pixels with Decomposition Model,” IEEE Transactions on Circuits and Systems for Video Tech., 20(11): 1648-52. [GCM Rank 1 in Multimedia, JCR Q1].
  • Paul, M., Frater, M., and Arnold, J. (2009), “An efficient Mode Selection Prior to the Actual Encoding for H.264/AVC Encoder,” IEEE Transactions on Multimedia, 11(4):581–88. [CORE A, Rank 2 in Multimedia].
  • Paul, M., Murshed, M. (2007), “An optimal content-based pattern generation algorithm,” IEEE Signal Processing Letters, 14(12):904-7. [CORE A]
  • Paul, M., Murshed, M. (2007), “Efficient H.264/AVC video encoder where pattern is used as extra mode for wide range of video coding,” Springer LNC, Vol. 4352, pp. 353-362. [SJR Q2]
  • Paul, M., Murshed, M., and L. Dooley (2005), “A real-time pattern selection algorithm for very low bit-rate video coding using relevance and similarity metrics,” IEEE Transactions on Circuits and Systems for Video Technology, 15(6):753–61.  [Rank 1 in Multimedia, JCR Q1].
  • Paul, M., Murshed, M. (2005), “Advanced Very Low Bit Rate Video Coding Using Preferential Pattern Selection Algorithms,” Journal of Research and Practice in Infor. Tech., 37(2): 89-99. [CORE B]
  • Paul, M., Murshed, M. (2005), “An efficient similarity metric for pattern-based very low bit-rate video coding,” Journal of Internet Technology, 6(3): 337-44 [JCR Q2]
  • M. Paul, and M. Murshed (2004), “Impact of similarity threshold on arbitrary shaped pattern selection very low bit-rate video coding algorithm,” Lecture Note in Computer Science, SJR Ranked Q2.

International Conference Publications (from 2009):

  • P. Bhatkoti and M. Paul, “The Appropriateness of k-Sparse Autoencoders in Sparse Coding,” IEEE International Conference on Electrical, Electronics, Computers, Communication, Mechanical and Computing (EECCMC), Tamil Nadu, India
  • Zhalong Hu, Abeer Alsadoon, Manoranjan, Paul, P.W.C. Prasad, and Salih Ali (2018), “Early Stage Oral Cavity Cancer Detection: Anisotropic Pre-Processing and Fuzzy C-Means Segmentation,” The 8th IEEE Annual Computing and Communication Workshop and Conference (IEEE CCWC), Las Vegas, USA.
  • P. Gao, W. Xiang, D. M. M. Rahaman, M. Paul (2017), “Joint texture and depth map coding for error-resilient 3-D video transmission,” IEEE International Conference on Image Processing (ICIP 2017). Rank 5 in Multimedia among all conferences and journals (GCM)
  • Vayalil, N. C., Paul, M., Kong, Yinan, (2017), “Novel angle-restricted test zone search algorithm for performance improvement of HEVC,” IEEE International Conference on Image Processing (ICIP 2017). Rank 5 in Multimedia among all conferences and journals (GCM)
  • T. A. Soomro, J. Gao, M. Paul, L. Zheng (2017), “Retinal Blood Vessel Extraction Method Based on Basic Filtering Schemes,” IEEE International Conference on Image Processing (ICIP 2017). Rank 5 in Multimedia among all conferences and journals (GCM)
  • DM. Rahman and M. Paul, (2017), "Adaptive Weighting between Warped and Learned Foregrounds for View Synthesize," IEEE International Conference on Multimedia and Expo (ICME 2017). Rank 11 in Multimedia among all conferences and journals (GCM)
  • K. Kalder and M. Paul, (2017), "Interband prediction of hyperspectral images using generalized regression neural network," IEEE International Conference on Multimedia and Expo (ICME 2017). Rank 11 in Multimedia among all conferences and journals (GCM)
  • MD. Salehin and M. Paul, (2017), " A Novel Framework for Video Summarization based on Smooth Pursuit Information from Eye Tracker Data ," IEEE International Conference on Multimedia and Expo (ICME 2017). Rank 11 in Multimedia among all conferences and journals (GCM)
  • MD. Salehin and M. Paul, L. Zheng (2017), “Affective Video Events Summarization using EMD Decomposed EEG Signals (EDES),” IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA-2017), Rank B, Accepted 1st September 2017.
  • T. A. Soomro, J. Gao, M. Paul, L. Zheng (2017), “Boosting Sensitivity of A Retinal Vessel Segmentation Algorithm With Convolutional Neural Network,” IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA-2017), Rank B, Accepted 1st September 2017.
  • Rahman, DM. M. and Paul, M (2017), “A Novel Virtual View Quality Enhancement Technique through a Learning of Synthesised Video,” IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA-2017), Rank B, Accepted 1st September 2017.
  • Podder, P. K., Paul, M, and Murshed, M.(2017), “A Novel Quality Metric Using Spatiotemporal Correlational Data of Human Eye Maneuver,” IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA-2017), Rank B, Accepted 1st September 2017.
  • DM. M. Rahman and M. Paul (2016), “View synthesised prediction with temporal texture synthesis for multi-view video,” IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA-2016), Rank B.
  • Md Salehin and M. Paul (2016), “Video summarisation using geometric primitives,” IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA-2016), Rank B.
  • K. K. Halder, M. Paul, M. Tahtali, S. G. Anavatti and M. Murshed (2016), “A Centroid Algorithm for Stabilization of Turbulence-Degraded Underwater Videos,” IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA-2016), Rank B.
  • T. A. Soomro, J. Gao, M. A. U. Khan, and M Paul (2016), “Automatic Retinal Vessel Extraction Algorithm,” IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA-2016), Rank B.
  • T. A. Soomro, J. Gao, M. A. U. Khan, T. M. Khan, M Paul, and N. Mir (2016), “Role of Image Contrast Enhancement Technique for Ophthalmologist as a Diagnostic Tool for the Diabetic Retinopathy,” IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA-2016), Rank B.
  • S. Shahriyar, M. Paul, and Manzur Murshed(2016), “Context-adaptive binary coding for hyperspectral images,” IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA-2016), Rank B.
  • T. Debnath, M. Paul, S. Chakraborty, P. Podder, R. Gururajan, A. Beg (2016), “An experimental analysis of assessor specific bias in a programming assessment in multi-assessor scenarios utilizing an eye tracker,” The London International Conference on Education (LICE-2016).
  • S. Shahriyar, M. Manzur, M. Ali, and M. Paul, (2016), "Lossless Depth Map Coding Using Binary Tree Based Decomposition and Context-Based Arithmetic Coding," IEEE International Conference on Multimedia and Expo (ICME 2016). Accepted 12th March 2016. Rank 10 in Multimedia among all Journals and Conferences (Google Metrics). Top 10% paper in the conference.
  • MD. Salehin and M. Paul, (2016), "Human visual field based saliency prediction method using eye tracker data for video summarisation," IEEE International Conference on Multimedia and Expo (ICME 2016). Rank 10 in Multimedia.
  • P. Podder, M. Paul, and M. Murshed, (2016), "A novel depth edge prioritization based coding technique to boost-up HEVC performance," IEEE International Conference on Multimedia and Expo (ICME 2016). 2016. Rank 10 in Multimedia.
  • D. M. Rahaman and M. Paul, (2016), "Hole-filling for single-view plus-depth based rendering with temporal texture synthesis," IEEE International Conference on Multimedia and Expo (ICME 2016). Rank 10 in Multimedia
  • Podder, P., Paul, M. and Murshed, M. (2016), “QMET: A New Quality Assessment Metric for No-Reference Video Coding by Using Human Eye Traversal,” IEEE 31th International Conference on Image and Vision Computing New Zealand (IVCNZ-2016), CORE B.
  • Bhatkoti, P. and Paul, M. (2016), “Early Diagnosis of Alzheimer’s Disease: A Multi-class Deep Learning Framework with Modified k-sparse Autoencoder Classification,” IEEE 31th International Conference on Image and Vision Computing New Zealand (IVCNZ-2016),  CORE B.
  • S. Chakraborty, S. Zhou, A. Hafeez-Baig, R. Gururajan, M. Paul, A. Mandal and A. Elizabeth Chako, (2016), " Objective Analysis of Marker Bias in Higher Education," IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE-2016), Bangkok
  • P. Podder, M. Paul, and M. Murshed, (2015), "Spatial Salient and Foreground Motion-based Efficient HEVC Video Coding," 30th IEEE International Conference on Image and Vision Computing New Zealand (IVCNZ-2015). Rank B.
  • D. M. Rahaman and M. Paul, (2015), "Free View-Point Video Synthesis Using Gaussian Mixture Modelling," 30th IEEE International Conference on Image and Vision Computing New Zealand (IVCNZ-2015). Rank B, Citation [2].
  • R. Xiao, M. Paul, and T. Bossomaier (2015), “Hyperspectral Image Coding using Spectral Prediction Modelling in HEVC Coding Framework,” 30th IEEE International Conference on Image and Vision Computing New Zealand. Rank B
  • M. Z. Parvez and M. Paul, (2015), "Epileptic Seizure Prediction Focusing on Relative Change in Consecutive Segments of EEG Signal," 17th International Conference on Bioinformatics and Biological Engineering (ICBBE-2015). Rank A
  • S. Shahriyar, M. Manzur, M. Ali, and M. Paul, (2015), " A Novel Depth Motion Vector Coding Exploiting Spatial and Inter-component Clustering Tendency," IEEE International Conference on Visual Communications and Image Processing (VCIP-2015). Rank B, Citation [1]. Rank 20 in Multimedia.
  • M. Z. Parvez and M. Paul, (2015), "Epileptic Seizure Prediction by Exploiting Signal Transitions Phenomena," 17th International Conference on Bioinformatics and Biological Engineering (ICBBE-2015). Rank A
  • P. Podder, M. Paul, T. Debnath, and M. Murshed, (2015), "An Analysis of Human Engagement Behaviour Using Descriptors from Human Feedback, Eye Tracking, and Saliency Modelling," IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA-2015), DOI: 10.1109/DICTA.2015.7371227, Rank B. Best paper in the ‘new research direction’ category. CORE Rank B.
  • MD. Salehin and M. Paul, (2015), "Summarizing Surveillance Video by Saliency Transition and Moving Object Information," IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA-2015), DOI: 10.1109/DICTA.2015.7371311, Rank B.
  • M. Z. Parvez and M. Paul, (2015), "Epileptic Seizure Prediction by Extracting Relative and Fine Changes of Signal Transitions," IEEE Engineering in Medicine and Biology Society (EMBC-2015), Rank A.
  • M. Z. Parvez and M. Paul, (2015), "Seizure Prediction by Analyzing EEG Signal based on Phase Correlation," IEEE Engineering in Medicine and Biology Society (EMBC), pp. 2888-2891, DOI: 10.1109/EMBC.2015.7318995. Rank A, Citation [1].
  • Ali, M., Shahriyar, S., Murshed, M., and Paul, M. (2015), “Lossless Image Coding using Binary Tree Decomposition of prediction residuals,” IEEE Picture Coding Symposium, pp. 194-198, DOI: 10.1109/PCS.2015.7170074. Rank 19 in Multimedia.
  • Shahriyar, S., Murshed, M., Ali, M., and Paul, M. (2015), “Cuboid coding of depth motion vectors using binary tree based decomposition,” IEEE Data Compression Conference (DCC), pp. 469, 1DOI: 0.1109/DCC.2015.43. Rank A, Citation [2]. Rank 11 among all journal & Conferences in Information Theory discipline according to Google Scholar Metrics. Rank 11 in Information Theory.
  • Podder, P., Paul, M., and Murshed, M. (2015), “Efficient coding strategy for HEVC performance improvement by exploiting motion features,” 40th IEEE International Conferences on Acoustics, Speech, and Signal Processing (ICASSP), pp. 1414-1418, Rank B, Citation [1]. Rank 5 in Signal Processing.
  • P. Podder, M. Paul, and M. Murshed (2015), " Fast Inter-Mode Decision Strategy for HEVC on Depth Videos," IEEE International Conference on Computer and Information Technology (ICCIT), pp. 288-293, DOI: 10.1109/ICCITechn.2015.7488084, [Citation 1].
  • M. Paul, S. Chakraborty, and M. Murshed (2015), "Joint Texture and Depth Coding using Cuboid Data Compression," IEEE International Conference on Computer and Information Technology (ICCIT), pp. 138-143.
  • MD Salehin and M. Paul (2015), "An Efficient Method for Video Summarization using Moving Object Information," IEEE International Conference on Computer and Information Technology (ICCIT), pp. 237-242.
  • P. Podder, M. Paul, and M. Murshed (2014), “Efficient HEVC Scheme using Motion Type Categorization,” ACM VideoNext: Design, Quality and Deployment of Adaptive Video Streaming in 10th International Conference on Emerging Networking Experiments and Technologies (CoNEXT), pp. 41-42, doi: 10.1145/2676652.2683462,  Rank A.
  • S. Chakraborty, M. Paul, M. Murshed, and M. Ali (2014), “A Novel Video Coding Scheme using a Scene Adaptive Non-Parametric Background Model,” IEEE Multimedia Signal Processing (IEEE-MMSP), pp. 1-6, Rank B, Citation [14].
  • S. Shahriyar, M. Ali, M. Murshed, and M. Paul (2014), “Inherently Edge-Preserving Depth-Map Coding Without Explicit Edge Detection and Approximation,” IEEE International Conference in Multimedia and Expo (IEEE-ICME), pp. 1-6, DOI: 10.1109/ICMEW.2014.6890592, Rank B, Citation [2]. Rank 11 in Multimedia
  • S. Chakraborty, M. Paul, M. Murshed, and M. Ali (2014), “An efficient video coding technique using a novel non-parametric modelling,” IEEE ICME, pp. 1-6, DOI: 10.1109/ICMEW.2014.6890590, Rank B, Citation [14]. Rank 11 in Multimedia.
  • P. Podder, M. Paul, M. Murshed, and S. Chakraborty (2014), “Fast Intermode Selection for HEVC Video Coding Using Phase Correlation”, IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA), pp. 1-8, Rank B, Citation [8].
  • S. Shahriyar, M. Ali, M. Murshed, and M. Paul (2014), “Efficient Depth Coding By Exploiting Temporal Correlations in Depth Maps”, IEEE DICTA, pp. 1-8, DOI: 10.1109/DICTA.2014.7008105, Rank B, Citation [3].
  • M. Z. Parvez and M. Paul (2013), “EEG Signal Classification using Frequency Band Analysis towards Epileptic Seizure Prediction,” IEEE International Conference on Computer and Information Technology (IEEE ICCIT-13), pp. 126-130, 2013, Rank C, Citation [3].
  • M. Paul, Christopher Evans, Manzur Murshed (2013), "Disparity-adjusted 3D multi-view video coding with dynamic background modelling," IEEE International Conference on Image Processing, pp. 1719-1723, Rank B, Citation [13]. Rank 5 in Multimedia
  • M. Z. Parvez and M. Paul (2013),“Classification of Ictal and Interictal EEG Signals,” 10th IASTED International conference on Biomedical Engineering, 2013. Rank A, Citation [4].
  • M. Z. Parvez and M. Paul (2012),“Features Extraction and Classification for Ictal and Interictal EEG Signals using EMD and DCT,” IEEE International Conference on Computer and Information Technology (IEEE ICCIT-12), pp. 132-137, Rank C, Citation 8].
  • M. Paul, J. Gao, M. Antolovich,and T. Bossomaier (2012), “Multi-view video compression using dynamic background frame and 3D motion estimation,” IEEE Int. Conference on Computer and Information Technology (IEEE ICCIT), pp. 84-89, Rank C, Citation [3].
  • Junbin Gao, M. Paul, and Jun Liu (2012), “The Image Matting Method with Zero-One Regularization,” IEEE International Conference on Multimedia and Expo (IEEE ICME-12), 2012. Rank B, Citation [3]. Rank 11 in Multimedia.
  • M. Paul, Junbin Gao, and Michael Antolovich (2012),“3D motion estimation for 3D video coding,” IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP), 2012, Rank B, Citation [5]. Rank 5 in Signal Processing
  • M. Paul and W. Lin (2011), “Efficient Video Coding Considering a Video as 3D Data Cube,” IEEE International Conference on Digital Image Computing: Techniques and Applications (IEEE DICTA), Rank B, Citation [2].
  • M. Paul, W. Lin, C. T. Lau, and B. –S. Lee (2011), “McFIS in hierarchical bipredictive picture-based video coding for referencing the stable area in a scene,” IEEE International Conference on Image Processing (IEEE ICIP), 2011, Rank B, Citation [10].
  • M. Paul, W. Lin, C. T. Lau, and B. –S. Lee (2010), “Pattern based video coding with uncovered background,” IEEE International Conference on Image Processing (IEEE ICIP), pp. 2065-2068, 2010, Rank B, Citation [2]. Rank 5 in Multimedia.
  • Liu, W. Lin, M. Paul, and F. Zhang (2010), “Enhanced just noticeable difference (JND) estimation with image decomposition for separating edge and textured regions,” IEEE Conference on Image Processing (IEEE ICIP), pp. 317 – 320, 2010, Rank B, Citation [4]. Rank 5 in Multimedia.
  • Z. Gu, W. Lin, C. T. Lau, B. –S. Lee, and M. Paul (2010), “Two dimensional singular value decomposition (2D-SVD) based video coding,” IEEE Int. Conference on Image Processing (IEEE ICIP), pp. 181 – 184, Rank B, Citation [4]. Rank 5 in Multimedia
  • Deng, W. Lin, C. T. Lau, B. –S. Lee, and M. Paul (2010), “Comparison between H.264/AVC and motion JPEG2000 for super-high definition video coding,” IEEE International Conference on Image Processing (IEEE ICIP), pp. 2037 – 2040, 2010, Acceptance Rate 44%, Rank B, Citation [5]. Rank 5 in Multimedia
  • Liu, W. Lin, M. Paul, and F. Zhang (2010), “Optimal compression plane (OCP)– A new framework for H.264 video coding,” IEEE Conference on Multimedia and Expo (IEEE ICME), pp. 456 - 461, 2010, Rank B. Rank 11 in Multimedia.
  • M. Paul, W. Lin, C. T. Lau, and B. –S. Lee (2010), “McFIS: better I-frame for video coding,” IEEE International Conference on Acoustics, Speech, and Signal processing (IEEE ISCAS), pp. 2171-2174, 2010, Rank B, Citation [7].
  • M. Paul, W. Lin, C. T. Lau, and B. –S. Lee (2010), “Video coding using the most common frame in scene,” IEEE International Conference on Acoustics, Speech, and Signal processing (IEEE ICASSP), pp. 734–737, 2010 , Rank B, Citation [17]. Rank 5 in Signal Processing.
  • M. Paul and M. Murshed (2009), “A novel pattern identification scheme using distributed video concept,” IEEE International Conference on Acoustics, Speech, and Signal processing (IEEE ICASSP), pp. 729-732, 2009, Rank B. Rank 5 in Signal Processing.

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