| Prof. Zhenghao ShiXi’an University of Technology, China (IEEE Senior Member)Shi Zhenghao, Ph.D., Professor, Doctoral Supervisor, Member of the Academic Committee of Xi'an University of Technology, Outstanding Member of CCF, IEEE Senior Member, "500 Elite Talents" of Taizhou City, Zhejiang Province, Executive Director of Shaanxi Computer Society, Chairman of the "Computer Vision Technology Professional Committee" of Shaanxi Computer Society, Vice Chairman of the "Biomedical Intelligent Computing Professional Committee" of Shaanxi Computer Society, Head of the "Intelligent Image Processing and Application" research team at Xi'an Technological University, with main research directions in machine vision, medical image processing, and machine learning. Published 60 academic papers as first author or corresponding author, authorized 15 invention patents (including 1 South African invention patent), won 2 second prizes of Shaanxi Science and Technology Progress Award (ranked first), 1 second prize of Xi'an Science and Technology Progress Award (ranked first), and 3 second prizes of Shaanxi Higher Education Science and Technology Award (ranked first). Firstly, One second prize for scientific and technological progress from Shaanxi Computer Society (ranked first), one first prize for technological invention from Shaanxi Computer Society (ranked first), and the "Wiley China Open Science High Contribution Author" award. Title: Wide Area Object Detection and Tracking Method Based on Deep Learning Abstract: Based on the research tasks undertaken by our research group in the past two years, we will explore the key issues of wide area object detection and tracking based on deep learning, and report our work on detecting and recognizing wide area objects using deep convolution and Transformer technology. |
Assoc. Prof. Jun WangShanghai University, China (IEEE Senior Member)Jun Wang is an Associate Professor with the School of Communication and Information Engineering, Shanghai University, Shanghai, China. He is a Senior Member of IEEE and CCF. He worked as a research scientist in the Department of Computing, the Hong Kong Polytechnic University in 2010, and as a postdoctoral fellow in the IDEA Lab, The University of North Carolina at Chapel Hill (UNC-CH), Chapel Hill, NC, USA from 2016-2017. His research interests include medical image analysis, computer vision, and pattern recognition. He has published more than 80 peer-reviewed papers in the international journals and conference proceedings. Title: Building Computer Aided Diagnosis Models for Autism Spectrum Disorder in Complex Scenarios Abstract:Autism Spectrum Disorder (ASD) is one of the most complex brain diseases, and its pathogenesis is still unclear. Building ASD computer aided diagnosis models is one effective approach for this task. However, it still faces many challenges, mainly involving complex data sources, diverse modalities, strong heterogeneity, and other aspects. This report takes this as a starting point to systematically introduce the recent research achievements of our group in this field. |
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