Exploring the Future: Emerging Trends in Robotics and AI

Conference Proceedings of 2025 5th International Joint Conference on Robotics and Artificial Intelligence
Erscheinungsjahr 2026
ISBN: 978-3-032-12756-3
Verlag: Springer

Buch, Englisch, 228 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 376 g

Reihe: Lecture Notes in Networks and Systems

This book contains the contributions presented on the 5th International Joint Conference on Robotics and Artificial Intelligence—JCRAI 2025. It reflects the emerging trends, and experimental results in the field of Robotics and AI, which covers abundant state-of-the-art research theories and ideas. Robotics and AI are two critical research areas with significant relevance to current advancements across various technological domains. The conference covers topics related to robotics and AI, encompassing machine learning, automation, robotics, deep learning, optimization algorithms, object detection, fault diagnosis, etc. The goal of the conference is to provide a major interdisciplinary forum for researchers, engineers, academics, and industry professionals to present the most innovative research and development in the field of Robotics and AI. The volume will serve as a valuable resource for researchers and graduate students working in the areas of Robotics and AI.

Zielgruppe

Research

Autoren/Hrsg.

Cheng, Li

Zhou, Tao

Zhang, Yanning

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik

Über Autor(innen)

Prof. Li Cheng Li Cheng is a Professor in the Department of Electrical and Computer Engineering at the University of Alberta. Before joining the University of Alberta, Dr. Cheng worked at ASTAR, Singapore, TTI-Chicago, USA, and NICTA, Australia. He earned his BSc in Computer Science from Jilin University, an M. Eng. from Nankai University, and a PhD in Computing Science from the University of Alberta. His research focuses on computer vision, multimedia data analytics, and applications. He has published over 150 research papers. He serves as AE for IEEE Transactions on Multimedia, IEEE Transactions on Circuits and Systems for Video Technology, Computer Vision and Image Understanding, Pattern Recognition. He is an elected member of two IEEE Signal Processing Technical Committees, Multimedia Signal Processing Technical Committee (MMSP TC) and Image, Video, and Multidimensional Signal Processing Technical Committee (IVMSP TC).
 
Prof. Tao Zhou Tao Zhou is currently a professor in School of Computer Science and Engineering, North Minzu University, Yinchuan, China. He is also a Ph.D. Supervisor in Institute for Medical Informatics, University of Huaqiao, Fuzhou, China. He obtained his PhD degree from Computer Science and technology, Northwestern Poly-technology Univ. in China. he has been a visiting scholar in The University of Leicester, UK. Chinese University of Hong Kong, HK, ShanDong University, China. His research interests include pattern recognition, machine learning, machine vision, medical image analysis. He has published over 220 academic papers in top journal or conference, such as Information Fusion, Applied Soft Computing, CIBM, CMPB, BSPC, Acta Electronica Sinica, et. al., 3 ESI Papers. he has published 3 books, Furthermore, he has obtained 6 authorized patents.
 
Prof. Yanning Zhang Yanning Zhang, a professor and doctoral supervisor at Northwestern Polytechnical University, is a Chang Jiang Scholar, a leading talent in the "Ten-Thousand Talents Program," and a recipient of the National Innovation First Prize. She is currently the vice president of Northwestern Polytechnical University. Prof. Zhang has led over 40 national-level projects, including the 973 and 863 Programs, and has published over 150 papers in top journals and conferences like IEEE TPAMI, IEEE TIP, IJCV, CVPR, and ICCV. Her research of interest mainly focuses on image processing, pattern recognition, and computer vision.