Keynote Speakers

Road environment recognition is essential for intelligent transportation systems, advanced driver-assistance systems, autonomous driving, traffic safety, and smart vehicular applications. Real-world road scenes are complex because traffic signs may be small or damaged, road markings may be degraded, road surfaces may contain cracks or potholes, and nighttime conditions may reduce visibility. This keynote speech presents AI-based visual scene understanding methods for road environment recognition. It introduces deep learning and computer vision approaches for traffic sign recognition, road marking detection, road damage analysis, road intersection detection, license plate recognition, and image-based road scene interpretation. YOLO-based detection models, spatial pyramid pooling, image enhancement, GAN-based data generation, and explainable AI are discussed as key techniques for improving accuracy, robustness, and interpretability. The talk also shares practical research outcomes from Taiwan road environment recognition and discusses future directions, including edge AI, real-time perception, trustworthy AI, multimodal sensing, and smart vehicular intelligence. The goal is to move from object detection toward comprehensive visual scene understanding for safer and more sustainable transportation systems.

Dr. Rung-Ching Chen is a Distinguished Professor in the Department of Information Management at Chaoyang University of Technology, Taichung, Taiwan. He received his B.S. degree from the Department of Electrical Engineering and his M.S. degree from the Institute of Computer Engineering, both at the National Taiwan University of Science and Technology, Taipei, Taiwan. He received his Ph.D. degree in 1998 from the Department of Applied Mathematics, Computer Science Section, at National Chung Hsing University, Taiwan.

He has held several academic leadership positions at Chaoyang University of Technology, including Chair of the Department of Information Management from 2005 to 2007, Dean of the College of Informatics from 2007 to 2015, and Executive Director of the Institutional Research Office from 2015 to 2017. He served as President of the Taiwanese Association for Consumer Electronics from December 2012 to December 2014. He has been a Fellow of the Institution of Engineering and Technology (IET) since July 2011, and has served as Executive Director of the IET Taipei Network and as a member of IEEE-related steering committees. He has also served on review committees of Taiwan's National Science and Technology Council (NSTC) in the field of artificial intelligence.

His international experience includes serving as a visiting professor at the University of Central Florida, U.S.A., in 2012, as a visiting researcher at the University of Aizu, Japan, in 2017, and as a visiting scholar in Germany in 2022. He has led numerous enterprise, national, and international research projects and has published extensively, including many SCI-indexed journal articles. He has also served as an editor, associate editor, reviewer, and organizing chair for many journals and international conferences.

He has been listed among the World's Top 2% Scientists, including recognition in the fields of artificial intelligence, engineering, and operations research. His research interests include deep learning, machine learning, Internet of Things, data analytics, computer vision, intelligent transportation, smart city applications, and the practical deployment of artificial intelligence technologies.

Takeshi Fukusako has been a Professor at Kumamoto University, Kumamoto, Japan, since 2016. He received the B.E., M.E., and Ph.D. degrees in engineering from Kyoto Institute of Technology, Kyoto, Japan, in 1992, 1994, and 1997, respectively. In 1997, he joined Kumamoto University as a Research Associate and was promoted to Associate Professor in 2003. From 2005 to 2006, he was a Visiting Researcher at the University of Manitoba, Canada. He also served as a Visiting Associate Professor at the City University of Hong Kong, Hong Kong SAR, China, in 2015.

His current research interests include antenna design, particularly broadband antennas, circularly polarized antennas, electrically small antennas, and their applications, such as remote sensing.

He has been actively involved in organizing several international conferences, serving as a Technical Program Committee Co-Chair of the 2014 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM 2014) and as a General Co-Chair of the IEEE International Conference on Computational Electromagnetics (ICCEM 2017). In addition, he served as an Associate Editor of the IEICE Transactions on Communications from 2012 to 2016 and of the IEEE Transactions on Antennas and Propagation from 2015 to 2022. He also served as a member of the Administrative Committee (AdCom) of the IEEE Antennas and Propagation Society from 2019 to 2021.

He has received several awards such as IEICE Communications Society Distinguished Contributions Award in 2016, Outstanding Associate Editor of IEEE Trans Antennas and Propagation in 2017 and the Director-General's Award of the Kyushu Bureau of Telecommunications, Ministry of Internal Affairs and Communications, Japan, in 2022. He is a Senior Member of both IEEE and IEICE.

• Antenna Engineering
• Electromagnetic Engineering
• Microwave & Millimeter Wave Engineering