Invited Speakers

Zhiyong Qiu, Ph.D., Senior Engineer, Graduated from Xi'an Jiaotong University. He is currently a researcher at the National Key Laboratory of High-End Server Systems and a senior member of the China Computer Federation (CCF). His main research focuses on heterogeneous computing architectures, deep learning, and related fields. He serves as a reviewer for journals such as the International Journal of Systems Science and IEEE Transactions on Circuits and Systems. He has led three research projects, including a sub- project of the National Key R&D Program and the Shandong Provincial Natural Science Foundation. Additionally, he has participated in four major projects, including the 2030-New Generation Artificial Intelligence Major Project and the Shandong Provincial Natural Science Foundation Major Project. He has published 15 SCI/EI-indexed academic papers and holds 57 authorized Chinese invention patents.

Zhipan Wu completed his B.E. in Computer and Application from Xi’an University of Science and Technology, China in 1999, and later received his M.E. in Software Engineering from Central South University, Changsha, China, in 2006. Since 1999, he has been serving as a computer specialist at Huizhou University, Guangdong, China, where he focuses on research areas such as image processing, pattern recognition, and artificial intelligence. His contributions extend beyond his university role, as he has actively engaged with the academic community by serving as a Technical Committee Member for the International Conference on Pattern Recognition and Artificial Intelligence (PRAI), a Technical Program Committee Member for the International Conference on Electronic Information and Communication Technology (ICEICT), and as a reviewer for the Alexandria Engineering Journal (AEJ, SCI Q2). Zhipan Wu has an impressive publication record, with 40 high-level papers, 8 authorized patents, 7 software copyrights and 10 textbooks to his name, and has secured 20 research grants from provincial or municipal funding agencies, indicating his exemplary research capabilities.

Title: An Intelligent Detection Method for Lake Water Environments: Identification and Research of Plastic Bottles Based on the YOLO Series

Abstract: As global plastic pollution intensifies, freshwater resources such as lakes face serious threats from plastic bottles and other waste, significantly affecting water quality and ecosystem health. To effectively monitor and manage plastic bottle pollution in lake environments, this paper proposes an intelligent detection method based on YOLOv11. The method innovatively utilizes ChatGPT's DALL·E technology to generate a dataset of plastic bottle images tailored specifically for lake scenarios, and integrates it with the deep learning-based object detection algorithm YOLOv11 to achieve real-time identification and localization of plastic bottles. Experimental results demonstrate that the YOLOv11 model exhibits excellent performance in detection accuracy, real-time processing, and adaptability to complex environments, achieving an identification accuracy of 95.6%, significantly reducing false positives and false negatives. Through comprehensive testing and optimization, YOLOv11 has shown strong robustness under various lighting conditions and complex backgrounds, making it particularly suitable for deployment in remote and resource-constrained areas. This research not only provides novel technical support for monitoring water pollution but also offers innovative solutions for future intelligent environmental protection practices.

Jin Xie is an Assistant Researcher at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. She obtained her Ph.D. in Pattern Recognition and Intelligent Systems from the University of Chinese Academy of Sciences in 2022, and then completed her postdoctoral research at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. She focuses on the research and development of AI-driven intelligent rehabilitation systems and the intelligent analysis of neuropsychiatric diseases. As a key member of the project, she has presided over and participated in national-level projects such as the National Key Research and Development Program, the General Program/Youth Program of the National Natural Science Foundation of China, etc. As the first author/co-first author, she has published more than 10 high-quality academic papers in total, with a total of 337 citations. The single highest SCI citation is 204 times. Her achievements have been selected into the top 1% of ESI highly cited papers in the world, and she has won the most popular article of IEEE and the highly cited EI paper of Google Scholar. She has applied for 29 patents, 12 of which have been authorized. She has won the honors of "Top Ten Outstanding Postdoctoral Fellows" and "Guangming Science City Young Scientific and Technological Talents"; she has been invited to give academic reports at domestic top conferences in the fields of biomedical engineering/intelligent rehabilitation for many times; she also serves as a reviewer for many high-level international journals such as IEEE Trans and Frontiers, and a technical committee member of IEEE conferences; she is a core member of the key laboratory and a member of many academic societies.

Fanyu Zeng, Jiangsu Province Double Innovation Doctor, obtained his Ph.D. from the Research Center for Robotics at University of Electronic Science and Technology of China in June 2021. He is currently a faculty member at the School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications. He has previously served as a technical consultant at Huawei Company and is also a senior expert at the Jiangsu Provincial Engineering Technology Research Center for Machine Vision Online Image Inspection. He has long been engaged in research and teaching in the fields of embodied intelligence, computer vision, and deep reinforcement learning. He has published numerous academic papers in SCI/EI journals and conferences, and authored one academic monograph. As a key researcher, he has led or participated in several research projects, including the National Key Research and Development Program, the National Natural Science Foundation of China's joint fund and general projects.

Jun Zhou is a professor of Southwest University, China. His research focuses on computer vision, machine learning, and spectral analysis. His work mainly covers areas like image processing, high-resolution imaging, machine learning, and intelligent spectral analysis. He has published over 30 SCI/EI papers in high-impact journals like Instrumentation and Control, Automation Journal, Applied Intelligence, ACS Catalysis, Analytical Chemistry, Chemical Communications, and Journal of Colloid and Interface Science. He has served as a reviewer for top journals, including Advanced Functional Materials, Analytical Chemistry, Biosensors & Bioelectronics, and conferences like CVPR, AAAI, and ICCV.

Speech Title: Exploration of Computer Vision Teaching Methods Based on Multidisciplinary Integration
Abstract: We propose an innovative teaching framework for computer vision education grounded in multidisciplinary integration principles. By systematically reconstructing course content around cutting-edge research problems and methodologies, our approach enhances learners' capacity for innovation and complex problem-solving. Empirical evidence from course assessments (including performance metrics, project evaluations, and longitudinal surveys) confirms significant improvements in students' theoretical understanding, technical competencies, and interdisciplinary application skills.

Shizhe Zhou, obtained his Ph.D. from Dept. of mathematics of Zhejiang University and did his postdoc in INRIA France and University of Science and Techinology of China. He is currently a faculty member at the School of Computer Science and Electronic Engineering of Hunan University. He has long been working in research and teaching in the fields of computer graphics, computer vision, image processing and computational geometry. He has published numerous academic papers in SCI/EI journals and conferences including top journal and conference such as siggraph and cvpr. As a key researcher, he has led or participated in several research projects, including National Natural Science Foundation of China and Huxiang Youth Talent Research Fund.