Title：Deep Learning and Computer Vision: Emerging Applications
Summary：
Recent advancements in deep learning have enabled a wide range of real-world applications across multiple domains. This workshop aims to explore emerging applications whether in general deep learning domains or in computer vision. We welcome participants reporting their experimental results on these emerging applications, challenges they have faced, and their mitigation strategy on topics like,but not limited to:1. Biomedical applications: medical imaging; digital pathology; surgical vision; wearable healthcare; drug discovery
2. Surveillance applications: object detection; tracking; anomalous behavior analysis; deepfake detection
3. Environmental applications: disaster prediction; damage analysis; wildfire detection
4. Smart-city applications: traffic management; energy management
5. Other relevant applications
6. Mitigation to challenges: real-time efficiency; domain adaptation; online concept drift; interpretability; ethical considerations
By bringing together researchers and practitioners, this workshop provides a platform to discuss innovative solutions, practical challenges, and future directions in applying deep learning or computer vision techniques to real-world problems.
Keywords：Deep Learning; Computer Vision; Applications; Challenges
Chair：
Sichuan University, ChinaDr. Yuqi Ouyang is an assistant professor at Sichuan University. He received the Ph.D. from University of Warwick, and B.Eng. from Wuhan University. His research focuses on deep learning, computer vision, video analytics, time-series analysis with domain adaptation or online learning. He worked closely with video surveillance projects funded by DSTL, UK Ministry of Defense. He has published several papers on international journals and conferences such as TIP, ECCV, ICASSP. He has served as the reviewer for several major conferences and journals, including ECCV, WACV, IEEE TNNLS, TCSVT, TITS, TOCybernetics, SPL.
Chair：
Assoc. Prof. Guangwu QianSichuan University, ChinaGuangwu Qian received the Ph.D. degree in computer science from College of Computer Science, Sichuan University, China in 2017. Afterwards, he worked as a researcher leader of algorithm in AI Research Laboratory, Imsight Technology Co., Ltd., Shenzhen, China and postdoctoral fellow at The Chinese University of Hong Kong, Hong Kong, China and Peng Cheng Laboratory, Shenzhen, China respectively. He is currently an associate professor at Sichuan University-Pittsburgh Institute, Sichuan University, Chengdu, China. His research interests include conceptors, medical imaging and deep learning.
