Prof. Lei Zhang

Chongqing University, China

(H-index: 71)(IEEE Senior Member)

Dr. Lei Zhang received his Ph.D degree in Circuits and Systems from the College of Communication Engineering, Chongqing University, Chongqing, China, in June 2013. From June to September 2013, he is a research visitor in Tsinghua University (Shenzhen) and Harbin Institute of Technology (Shenzhen). He was selected as a Hong Kong Scholar in China in 2013, and worked as a Post-Doctoral Fellow with The Hong Kong Polytechnic University, Hong Kong, from 2013 to 2015. He is a senior visiting professor in University of Macau from 2017 to 2018. He is currently a Full Professor at the School of Microelectronics and Communication Engineering, Chongqing University, China. He is the director of the Chongqing Key Laboratory of Bio-perception and Multi-modal Intelligent Information Processing, and the leader of Learning Intelligence and Visual Essential Group (LiVE Group). He is an IEEE Senior Member, CCF Distinguished Member and ACM member. He is included in the World Top 2% Scientists List released by Stanford University and Elsevier (全球前2%顶尖科学家终身科学影响力和年度影响力双榜单).

His research interests include computer vision, machine learning, pattern recognition and intelligent systems. He has authored more than 150 scientific papers in many top journals such as IEEE Trans. Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, IEEE Trans. Image Processing, IEEE Trans. Neural Network and Learning Systems, IEEE Trans. Multimedia, IEEE Trans. Cybernetics, IEEE Trans. Circuits and Systems for Video Technology, IEEE Trans. Instrumentation and Measurement, IEEE Trans. Systems, Man, and Cybernetics: Systems, IEEE Trans. Geoscience and Remote Sensing, IEEE Sensors Journal, Pattern Recognition, Information Sciences, Information Fusion, Cognitive Computation, Neurocomputing, Sensors and Actuators B: Chemical, Analytica Chimica Acta, and top conferences such as CVPR, ICCV, ECCV, ICML, ACM MM, AAAI, IJCAI, etc. 10 papers are selected as Highly Cited papers and Hot papers by Thomson Reuters. He has authored 1 English Monograph published in Springer and 14 Chinese invention patents. He serves as an Associate Editor for IEEE Transactions on Instrumentation and Measurement, Neural Networks and CAAI Trans. Intelligence Technology, etc. He has been a reviewer for more than 50 journals, such as Nature Electronics, IEEE T-PAMI, IJCV, IEEE T-IP, IEEE T-NNLS, IEEE T-MM, IEEE T-CSVT, IEEE T-IM, IEEE T-SMCA, IEEE T-IE, IEEE T-CYB, IEEE T-CAS, IEEE Sensors Journal, IEEE GRSL, Pattern Recognition, Information Fusion, Information Sciences, Neural Networks, Neurocomputing, Expert Systems with Applications, Knowledge Based Systems etc. He has also been the keynote speaker, conference co-chair, regional chair, session chair and best paper award evaluation committee chair for many internetional conferences, such as CVPR, ICCV, ECCV, ACM MM, ICML, NeurIPS, AAAI, IJCAI, ICLR, ICME, IEEE ICCT2017-2018, IEEE TENCON, IEEE SSCI, ELM, ITA, WCSN, etc.

Dr. Zhang is recipient of ACM SIGAI Rising Star Award, a recipient of Best Paper Award by Chinese Conference on Biometric Recognition in 2017, Outstanding Reviewer Awarded by many Journals, Chongqing Natural Science Excellent Academic Paper Award in 2016, Outstanding Doctoral Dissertation Award of Chongqing, China, in 2015, Hong Kong Scholar Award in 2014, Academy Award for Youth Innovation of Chongqing University in 2013 and the New Academic Researcher Award for Doctoral Candidates from the Ministry of Education, China, in 2012.

Title: A story of transfer learning: theory, algorithms and recent progress
Abstract:Transfer learning, as a mainstream branch of deep learning, has been widely used in artificial intelligence, such as natural language processing, computer vision and multimodal large models. In this talk, I will give a story of transfer learning about its concept, theory and algorithms. Then I introduce our recent progress on transfer learning algorithms toward solving some important problems in computer vision, such as image classification, object detection, segmentation, adversarial defense, etc.

Prof. Chuan Qin

University of Shanghai for Science and Technology, China

(H-index: 42)

Chuan Qin received his Ph.D. degree in signal and information processing from Shanghai University, Shanghai, China, in 2008. Since Dec. 2008, he has been with the faculty of University of Shanghai for Science and Technology, where he is currently a Professor. He was with Feng Chia University at Taiwan as a Postdoctoral Researcher from July 2010 to July 2012. His research interests include multimedia intelligent computing, AI security, data hiding and image processing in encrypted domain. He has published over 200 peer-reviewed papers in journals and conferences, such as IEEE TIP, IEEE TIFS, IEEE TMM, IEEE TCSVT, and ACM MM. He has also published one book and held seven authorized patents. He was selected as the Highly Cited Chinese Researchers by Elsevier in 2020 and the World’s Top 2% Scientists in 2020-2024. He won the Excellent Paper Awards of CIHW 2016 and ChinaMFS 2023, and the Candidate of Excellent Paper Award of IEEE IIHMSP 2014. He has served as the Associate Editor for ACM TOMM, Neural Networks (Elsevier) and Information Fusion (Elsevier). 

Title: Image Copy Detection Based on Perceptual Hashing

Abstract: Nowadays, Image copy detection is an important task on Internet and social media platform, which can be effectively used to achieve image copyright protection and authentication. In this talk, we will focus on how to realize image copy detection with perceptual hashing technique. First, the concept of perceptual hashing and its differences with cryptographic hash function and semantic retrieval hashing are given. Then, representative methods of perceptual image hashing for copy detection are introduced detailedly, including traditional methods and deep learning-based methods. Finally, the summary and further research directions are discussed.

Prof. Azlan Mohd Zain

Universiti Teknologi Malaysia, Malaysia

(H-index: 38)

Azlan Mohd Zain (Member, IEEE) received the master’s degree in science (productivity and quality improvement) from Universiti Kebangsaan Malaysia (UKM) and the Ph.D. degree in computer science from Universiti Teknologi Malaysia (UTM), in 2010. He is currently a Professor with the Faculty of Engineering, School of Computing, UTM. He is also the Director of the UTM Big Data Research Centre. As an academic staff, he has successfully supervised more than 25 postgraduate students and received more than 20 research grant funding to support research students. He has published more than 100 research papers. He has been invited as keynote speaker at over five international conferences, serves on numerous committees, and has served on editorial board for three international journals.

Title: The Role of Artificial Intelligence (AI) in Computer Vision

Abstract: The topic of artificial intelligence (AI) and computer vision is covered in this sharing session. Artificial Intelligence is a technique that allows machines and computers to perform computer vision tasks intelligently. A subset of artificial intelligence (AI) called machine learning (ML) uses algorithms to provide AI applications. A subset of machine learning (ML) called deep learning (DL) is used to tackle increasingly challenging computer vision tasks. In this session, the significance of machine learning and deep learning for computer vision tasks such object recognition, object localization, segmentation, detection, and classification of images is discussed. This session concludes with a demonstration of a small computer vision project that uses an AI tool to detect image edges.

Prof. Liang Hu

Tongji University, China

Dr Liang Hu is a professor with Tongi University and also the Chief Al Scientist with DeepBlue Academy of Sciences, China. His research interests include recommender systems, machine leaming, data science and general intelligence. He has published a number of papers in top rank interational conferences and journals, including WWW, IJCAI, AAAL, ICDM, TOIS, TKDE, TNNLS. He has been invited as the program commitee members of more than 30 top-rank Al interational conferences, including AAAI, IJCAI, ICDM, CIKM, and KDD. He also serves as the reviewer of more than ten top-rank interational journals, including ACM CSUR, IEEE TKDE, ACM TOIS, IEEE TPAMl, etc. In addition,he has presented more than ten tutorials on recommender systems and machine leaing at top-rank Al conferences including IJCAl, AAAl, SIGIR, WWW and ICDM.