REGISTRATION INFORMATION IS NOW AVAILABLE
The IEEE International Conference on Signal and Image Processing Applications (ICSIPA), organized by the IEEE Signal Processing Society Malaysia Chapter, provides a forum for local and international researchers as well as engineers from academia and industry to present and discuss the latest technological advances and research results in the fields of theoretical, experimental and applied signal, image and video processing. In addition to advancing core research, IEEE ICSIPA 2026 emphasizes the application of signal processing technologies in addressing humanitarian challenges, including disaster response, healthcare, environmental monitoring, and sustainable community development. IEEE ICSIPA 2026 is therefore seeking original high-quality submissions that not only advance the state-of-the-art in signal, image and video processing, but also demonstrate meaningful impact in humanitarian technology and real-world applications.
Past ICSIPA conferences are indexed in Scopus. Papers presented in this conference will also be submitted for inclusion in IEEEXplore.
THEMES
IEEE ICSIPA 2026 is seeking original high research in the broad field of signal, image and video processing. Papers are solicited on, but not limited to:
- Acquisition, Storage, Retrieval and Display
- Applied Signal and Speech Processing
- Biomedical Signal Processing
- Computer Vision Processing and Analysis
- Information Forensics and Security
- Machine Learning for Signal and Image Processing
- Signal Processing for Humanitarian Technologies
- Trending Technologies in Signal and Image Processing
PAPER SUBMISSION
Submitted papers are to be in IEEE conference paper format up to 6 pages. All accepted and presented IEEE ICSIPA 2026 papers will be submitted to be indexed in IEEE Xplore.
Submitted papers are to be in IEEE conference paper format up to 6 pages.
Submission Link : https://edas.info/N34780
PAPER TEMPLATE
Microsoft Word
- A4 (DOC, 30 KB) Updated 2024
LaTeX
LaTeX Template Instructions (PDF, 63 KB) [Be sure to use the template’s conference mode.]
- Template (ZIP, 700 KB) Updated 2024
- LaTeX Bibliography Files (ZIP, 309 KB)
Overleaf
- When working in Overleaf, the template is available at https://www.overleaf.com/gallery/tagged/ieee-official
Important Dates:
Paper Submission Deadline : 30 April 2026 30 May 2026 15 June 2026 30 June 2026
Notification for Acceptance : From 30 May 2026
Early Bird Registration : 15 July 2026
Normal Registration Deadline : 7 August 2026
Camera Ready Submission : 7 August 2026
Conference : 8 – 10 September 2026
Download Call for Papers
REGISTRATION
– Each Normal registration allows one presenter to present up to two accepted papers.
– Online presentation is available for presenters with affiliations outside of Malaysia.
PAYMENT INFORMATION
Local delegates are encouraged to pay in Malaysian Ringgit (MYR). Payment is to be made to the conference account below (proof of payment and proof of IEEE/IEEE SPS Membership must be emailed to both loges@ieee.org and icsipa@ieee.org).
Account Name : IEEE MALAYSIA SIGNAL PROCESSING CHAPTER
Account Number : 8007470046
Bank : CIMB Bank Berhad, Cyberjaya branch, 63000 Cyberjaya, Selangor, Malaysia
Swift Code : CIBBMYKL
| REGISTRATION FEES | IEEE SPS Member | IEEE Member | Non Member | ||||
| MYR | USD | MYR | USD | MYR | USD | ||
| Earlybird | Normal | 1700 | 450 | 1900 | 500 | 2200 | 600 |
| Student | 1250 | 330 | 1400 | 370 | 1600 | 430 | |
| Participant | 1000 | 270 | 1100 | 300 | 1200 | 320 | |
| Normal Registration | Normal | 1910 | 505 | 2110 | 565 | 2410 | 645 |
| Student | 1410 | 375 | 1610 | 435 | 1710 | 455 | |
| Participant | 1000 | 270 | 1100 | 300 | 1200 | 320 | |
KEYNOTE 1 : Engaging Video Analytics and Generative AI
Abstract:
In this talk, Dr. Jianquan Liu presents an industry perspective on the convergence of video analytics and generative AI. The talk begins with an overview of video analytics, covering advancements in action recognition, object tracking, human-object interactions, scene recognition, and behavioral pattern analysis. These technologies enable efficient extraction, retrieval, visualization, and summarization of video content. The presentation then explores the impact of generative AI, particularly large language models (LLMs), on video understanding. It discusses how LLMs enhance object recognition, semantic segmentation, action recognition, captioning, visual question answering, and storytelling. Dr. Liu provides industry case studies to illustrate these applications while also addressing limitations and challenges. The talk introduces NEC’s narrative summarization framework, designed to tackle key challenges in video analytics. It concludes with a demonstration of “Video with LLM” technology, showcasing its practical application in automating traffic accident investigation reports. This presentation offers valuable insights into the current state and future potential of AI-driven video intelligence, bridging the gap between technical innovation and practical application for both industry professionals and general audiences.
Biography:
Jianquan Liu is currently a Director and Senior Principal Researcher at NEC Corporation, working on the topics of multimedia data processing. He is selected as IEEE SPS 2026 Distinguished Industry Speaker, and also a Visiting Professor at Nagoya University and an Adjunct Professor at Hosei University, Japan. Prior to NEC, he was with Tencent Inc. from 2005 to 2006. He has published 80+ papers at major international/domestic conferences and journals and filed 100+ PCT patents. He also successfully transformed these technological contributions into commercial products in the industry. For his industry contributions, Dr. Liu has received the Japan Minister of Economy, Trade and Industry (METI) Award as the highest honor for industry corporations at the 38th Advanced Technology Award in 2025, the 25th Anniversary Special Award at CEATEC AWARD 2024, the APSIPA 2024 Industrial Distinguished Leader, the DBSJ Young Researcher’s Achievement and Contribution Award 2024, the IEICE Achievement Award 2023, the ITE Niwa & Takayanagi Achievement Award 2023, the 69th Electrical Science and Engineering Promotion Award, and the Minister of Education, Culture, Sports, Science and Technology (MEXT) Award in 2021, the KANTO Invention and Innovation Award 2021, the IPSJ Research and Engineering Award 2020 and the IPSJ Industrial Achievement Award 2018. Currently, Dr. Liu is/was serving as a Member-at-Large of IEEE SPS Industry Board (2025-2026), the Industry Co-chair of IEEE ICIP 2023, 2025 and ACM MM 2023, 2024, 2025; the General Co-chair of IEEE MIPR 2021; the PC Co-chair of IEEE IRI 2022, ICME 2020, AIVR 2019, BigMM 2019, ISM 2018, ICSC 2018, etc. He is a senior member of ACM, IEEE, IEICE, and IPSJ, and a member of ITE, APSIPA and DBSJ, and an associate editor of IEEE TMM (2021-2024), ACM TOMM (2022-), EURASIP JIVP (2023-), IEEE MultiMedia Magazine (2019-2022), ITE Transaction on Media Technology and Applications (2021-), APSIPA Transactions on Signal and Information Processing (2022-), and the Journal of Information Processing (2017-2021). Dr. Liu received the M.E. and Ph.D. degrees from the University of Tsukuba, Japan.
KEYNOTE 2 : : Evolution of Group and Shuffle Networks for Advancing Deep Learning Architectures
Abstract:
The rapid evolution of deep learning has stimulated the design of highly effective convolutional neural network architectures that achieve strong performance in classification, object detection, and segmentation tasks while maintaining computational feasibility. Among these architectures, the incorporation of Group Convolution and Shuffle modules has emerged as an interesting solution for encouraging networks to learn unique sets of feature representations while maintaining competitive performance. This session aims to present an overview of the evolution of group and shuffle network architectures, highlighting their key developments, contributions, and impact on effective deep learning models. The concept of group convolution was introduced by dividing input channels into separate groups, enabling parallel feature extraction and encouraging networks to learn unique sets of feature representations from smaller subgroups. However, the application of standalone group convolution modules suffers from limited information exchange across channel groups, potentially restricting feature learning capabilities. To address this limitation, channel shuffling mechanisms were introduced to facilitate information exchange between groups. By rearranging feature channels across groups, the network is able to increase information diversity through effective cross-group information flow while preserving the computational benefits of group convolutions. Furthermore, several innovations in Group and Shuffle Networks consider practical hardware constraints such as memory access cost, network fragmentation, and parallelism. These improvements have resulted in enhanced inference speed and better performance on resource-constrained devices, including smartphones and embedded systems. Some of the improvements in group convolution that will be discussed include optimal group division, placement strategies, weighted channel division, and many others. In addition, several advancements in shuffling methods, such as random shuffle, attentive shuffle, channel-shift shuffle, and other variants, will also be explored. Overall, the progression from standard group convolutions to advanced group-and-shuffle-based architectures represents a significant milestone in improving the capabilities of deep learning models, offering a balance between accuracy, computational efficiency, and deployment practicality for modern artificial intelligence applications.
Biography:
Dr. Mohd Asyraf Zulkifley is currently a Professor of Artificial Intelligence in the Department of Electrical, Electronic and Systems Engineering at Universiti Kebangsaan Malaysia (UKM). He completed his undergraduate studies in seven semesters with First Class Honours at the International Islamic University Malaysia under the Yayasan Proton Scholarship, before pursuing his Ph.D. at the University of Melbourne, where he submitted his thesis within three years. After returning to UKM, he received several prestigious awards, including the University Excellent Service Award, MyRA Research Excellence Award, Research Group Excellence Award, Excellent Junior Teaching Award, Turkish Burslari Scholarship, and the Anugerah Bitara: Ahli Akademik Harapan UKM. He later served as a postdoctoral researcher in the Department of Computer Science at the University of Oxford for two years, working under the guidance of Prof. Niki Trigoni. Prof. Zulkifley has actively collaborated with international researchers from countries including Korea, Indonesia, the Philippines, Australia, the United States, China, and Thailand. He has also secured multiple international research grants as Principal Investigator, including the NVIDIA Grant (USA), the Asia-Pacific Telecommunity Grant (funded by the Government of Korea), a Malaysia–Jordan matching grant, and the ISIF-Asia Grant (APNIC, Australia). In addition, he has been invited as a visiting fellow and research scholar by several renowned institutions, including MIMOS Sdn. Bhd. (Malaysia), the University of Melbourne (Australia), Sabancı University (Turkey), Universitas Indonesia (Indonesia), the Malaysian Space Agency (Malaysia), Universitas Syiah Kuala (Indonesia), and Rabdan Academy (United Arab Emirates). In 2021 and 2023, he was recognized among the Top 2% Scientists according to the Stanford–Elsevier global citation ranking. His current research interests focus on advancing artificial intelligence technologies for engineering applications.
KEYNOTE 3 : From Microscopes to Knowledge – How Trustworthy AI is Transforming Scientific Imaging
Abstract:
Scanning Electron Microscopy (SEM) plays a pivotal role in materials science, nanotechnology, and biological characterization by enabling high-resolution visualization of complex structures. However, the presence of noise and limited signal-to-noise ratio (SNR) remains a fundamental challenge, affecting image quality, measurement accuracy, and the reliability of subsequent scientific analysis. This keynote explores the emerging role of trustworthy artificial intelligence (AI) in enhancing SEM image quality while maintaining scientific integrity. Rather than focusing solely on visual improvement, we discuss AI-driven approaches that achieve a critical balance between effective noise suppression and preservation of essential structural information. Through SEM-based case studies, this keynote presents a human-in-the-loop paradigm where AI serves as an intelligent assistant to enhance scientific discovery while preserving the critical role of domain expertise. Again, this talk is to establish a reliable pathway from noisy SEM acquisitions to trustworthy, interpretable, and scientific knowledge.
Biography:
Prof Dr. Ir. Sim Kok Swee (Senior Member, IEEE) is currently a Professor with Multimedia University, Malaysia. He actively collaborates with various local and international universities and hospitals. He has filed more than 28 patents and 85 software copyrights. He is a fellow of the Academy of Sciences Malaysia (FASc), the ASEAN Academy of Engineering and Technology (FAAET) ,the Institution of Engineers Malaysia (FIEM), and the Institution of Engineering and Technology (FIET), U.K.
Over the years, he has received numerous prestigious national and international awards. These include Japan Society for the Promotion of Science (JSPS) Fellowship, the Top Research Scientists Malaysia (TRSM) Award from the Academy of Sciences Malaysia and Korean Innovation and Special Awards. He was a recipient of the TM Kristal Award and multiple World Summit on the Information Society (WSIS) Prizes.
📢 ICSIPA 2026 HANDS-ON AI WORKSHOP
Join us for a practical AI workshop:
🤖 Building LLM-Powered Applications on Commodity Computers
🎤 Trainer:
Dr. Ramesh Perumal
AI Solution Architect, Intel Penang
📅 10 September 2026
⏰ 9:00 AM – 5:00 PM
📍 Electronic Lab 1, UTeM, Melaka
💡 What you will learn:
✅ OpenVINO Deployment Workflow
✅ LLM Optimization Techniques
✅ Multimodal Chatbots
✅ Retrieval-Augmented Generation (RAG)
✅ Agentic AI Workflow
💰 Workshop Fee:
🎉 FREE for ICSIPA 2026 participants
💵 RM50 for non-ICSIPA participants
📝 Register by 9 September 2026:
https://forms.gle/ThDSgoD4EVvX52WQA
⚡ Limited seats available!
Please share with your students, colleagues and anyone interested in AI.
📞 Enquiries: 013-7475869
✉️ mnorzali@gmail.com
Conference Committee
General Chair
Syed Mohd Zahid Syed Zainal Ariffin
Vice-Chair
Siti Armiza Mohd Aris
Technical Program
Humaira Nisar
Mohammad Faizal Ahmad Fauzi
Secretariat
Nurul Japar
Haidawati Mohamad Nasir
Finance
Rajasvaran Logeswaran
Program
Zaid Omar
Publicity
Usman Ullah Sheikh
Publication
Hezerul Abdul Karim
Nurbaity Sabri
Local Arrangement
Raseeda Hamzah
Workshop
Mohd Norzali
Sponsorship
Norliza Mohd Noor
TBA
Revise your paper by taking into account the suggestions and corrections highlighted by the reviewers. Please ensure that the similarity rating for the camera-ready paper is below 30%.
Check the formatting of your paper. Please use the IEEE paper template provided at https://sps.ieeemy.org/icsipa2026/ under the SUBMISSION link. Do NOT use any other template. The length of the final paper should be no more than 6 pages in A4 size, including figures, tables and references. IMPORTANT: Please remove any header and/or footer in the manuscript. Please refer to the above link for further details.
Check the final manuscript (camera ready paper) to ensure that it is IEEEXplore compatible. Authors need to convert and check their final manuscript with PDF eXpressat https://ieee-pdf-express.org/(using conference ID: 69622X).
Register and pay the conference fees. Before you can upload the final manuscript (camera ready paper), at least one author of each paper must register for the conference.
Upload the checked final manuscript (camera ready paper) through EDAS. Please complete the IEEE Electronic Copyright Transfer Form (eCF)in EDAS by clicking on the copyright icon.
Papers that are not presented at the conference will also be excluded from official proceeding and will not be included in IEEE Xplore.
IEEE ICSIPA 2026 will be held at the Holiday Inn Melaka by IHG, Jalan Syed Abdul Aziz, 75000 Melaka, Malaysia
An International Branded Hotel in the Heart of Melaka’s UNESCO World Heritage City. Located along the scenic waterfront overlooking the Straits of Melaka, Holiday Inn Melaka is the ideal choice for leisure and business travellers seeking comfort, convenience, and warm hospitality. Just steps from Mahkota Parade, the hotel offers easy access to Melaka’s iconic attractions, including Menara Taming Sari, Jonker Street, Bukit Melaka, A Famosa, and the Melaka River Cruise. Complimentary scheduled shuttle services are available exclusively for in-house guests to selected nearby attractions. The hotel is also conveniently located approximately 2 hours from Kuala Lumpur.
