Osaka, Japan
Osaka, Japan
University of Leicester, United Kingdom
Prof. Huiyu Zhou received a Bachelor of Engineering degree in Radio Technology from Huazhong University of Science and Technology of China, and a Master of Science degree in Biomedical Engineering from University of Dundee of United Kingdom, respectively. He was awarded a Doctor of Philosophy degree in Computer Vision from Heriot-Watt University, Edinburgh, United Kingdom. Prof. Zhou currently is a Full Professor at School of Computing and Mathematical Sciences, University of Leicester, United Kingdom. He has published over 400 peer-reviewed papers in the field. He was the recipient of "CVIU 2012 Most Cited Paper Award", “MIUA 2020 Best Paper Award”, “ICPRAM 2016 Best Paper Award” and was nominated for “ICPRAM 2017 Best Student Paper Award” and "MBEC 2006 Nightingale Prize". Dr. Zhou serves as the Editor-in-Chief of Recent Advances in Electrical & Electronic Engineering and Associate Editor of IEEE Transaction on Human-Machine Systems, IEEE Journal of Biomedical and Health Informatics, Pattern Recognition, PeerJ Computer Science, Security and Safety, Scientific Reports, Machine Intelligence Research, International Journal of Image and Graphics and IEEE Access, and Area Chair of IJCAI, ICRA and BMVC. He has given over 100 invited talks at international conferences, industry and universities, and has served as a chair for 70 international conferences and workshops.
Nara Institute of Science and Technology, Japan
Professor Keiji Nakajima was awarded his Ph.D. from the Graduate School of Agriculture at Kyoto University in recognition of his research into the molecular basis and evolution of stereospecific alkaloid biosynthetic capacity. He subsequently shifted his field of expertise to plant developmental biology following his postdoctoral fellowship at New York University. Since that time, he has achieved a series of internationally renowned research achievements, including the discovery of intercellular movement of transcription factors and microRNAs that transmit short-range cell-cell signals to create elaborate plant tissue patterns, as well as the discovery of genes that confer pluripotency on plant cells. In recent years, he has been engaged in efforts to elucidate the genetic mechanisms that underpin the robust and plastic developmental characteristics of plant roots, employing a combination of live microscopic imaging, computer vision, and mathematical simulation. From 2019 to 2024, he served as the representative of the government-funded research consortium named "Periodicity and its Modulation in Plants", with the objective of accelerating interdisciplinary collaborative research in plant biology and information science.
Speech Title: "Uncovering Hidden Principles in Plant Developmental Regulation with Live Microscope Imaging and Computer Vision"
Abstract: The impact of integrating computational technology in basic biological research is most effectively illustrated by the evolution of bioinformatics over the past few decades. In recent years, there has been a growing trend towards utilizing the advanced technology of computer vision in medical diagnosis and in deepening our understanding of biological systems. The field of plant developmental biology is arguably one of the most suitable areas for accelerating research using computer vision, as the molecular and cellular dynamics of organisms undergoing normal development can be readily observed through live microscopic imaging. Over the past five years, I have led a research consortium, "Periodicity and its Modulation in Plants," which brought together over 40 principal investigators with expertise in plant biology, mathematical biology, computer vision, and human augmentation. The consortium aimed to uncover hidden principles in plant developmental regulations, providing foundation for the improvement of crops with enhanced yields and greater environmental resilience. In this presentation, I will highlight a few collaborative achievements of the consortium members that have successfully visualized hidden aspects of plant developmental regulation and gene functions, and discuss future directions in the collaboration of computer science and basic biological research.
Nara Prefectural University, Japan
Dr. Arata SUZUKI earned his Ph.D. in Information Science from Nara Institute of Science and Technology. Since 2021, he has been a professor at Nara Prefectural University, and in 2024, he became the Dean of faculty of area promotion. His career includes positions at Zojirushi Corporation and Wakayama University. Dr. Suzuki’s research focuses on statistical data analysis, Taguchi robust engineering, and biomedical data analysis. He is particularly dedicated to developing health assessment methods based on bio-signal analysis, with a special emphasis on photoplethysmography for health evaluation.
Speech Title: " Digital Medicine and Image Processing: The Past and Future"
Abstract: Due to the global shortage of medical professionals, the importance of Digital Medicine and Image Processing is increasing. New technologies are being developed to assist medical professionals, such as electronic medical records, IoT healthcare devices, and medical image diagnosis using AI. At the same time, digital medicine is also being used to support health in everyday life. One technology that everyone uses is the pedometer on their smartphone. These are used in health promotion insurance, where insurance premiums vary depending on the number of steps walked in a day. In this presentation, we will focus on the use of digital devices in our everyday lives, look back on the technology so-called Digital Medicine has developed so far, and discuss future prospects.
Beijing Language and Culture University, China
XiWen Zhang is currently a full professor of Digital Media Department, School of Information Science, Beijing Language and Culture University. Prof. Zhang worked as an associated professor from 2002 to 2007 at the Human-computer interaction Laboratory, Institute of Software, Chinese Academy of Sciences. From 2005 to 2006 he was a Post doctor advised by Prof. Michael R. Lyu in the Department of Computer Science and Engineering, the Chinese University of Hong Kong. From 2000 to 2002 he was a Post doctor advised by Prof. ShiJie Cai in the Computer Science and Technology department, Nanjing University. Prof. Zhang's research interests include pattern recognition, computer vision, and human-computer interaction, as well as their applications in digital image, video, and ink. Prof. Zhang has published over 60 refereed journal and conference papers. His SCI papers are published in Pattern Recognition, IEEE Transactions on Systems Man and Cybernetics B, Computer-Aided Design. He has published more than twenty EI papers. Prof. Zhang received his B.E. in Chemical equipment and machinery from Fushun Petroleum Institute (became Liaoning Shihua University since 2002) in 1995, and his Ph.D. advised by Prof. ZongYing Ou in Mechanical manufacturing and automation from Dalian University of Technology in 2000.
Speech Title: "Three Views on Intelligently Extracting and Generating Information from Image"
Abstract: Due to pattern recognition and deep learning, various information can be extracted and generated from image. Our work has focused on using the proposed hierarchy models, local homogeneity, and adversarial generation. Various digital images are processed, such as ones scanned from mechanical paper drawings and paper text, face images, portrait ones with line drawings, and microscopic bone marrow images. Various information is extracted using the proposed hierarchy models. Graphics and their multi-levels compounded objects are extracted and recognized from images scanned from mechanical paper drawings using a hierarchy model of engineering drawings. Faces and their components are extracted from photos using a facial model. Various information is extracted using the proposed local homogeneity. Karyocytes and their components from microscopic bone marrow images based on regional color features. Various information is extracted and generated from image using cycle-Consistent adversarial networks. Text is separated from grid background using cycle-Consistent adversarial networks. Digital images of Chinese classical upper-class lady paintings are generated from images with line drawings using conditional generative adversarial networks.
Osaka, Japan
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