2024年5月22日下午16：00，来自英国谢菲尔德大学的国际访问学者韩军功教授来我院作题为“When Deep Learning Meets Computer Vision: Challenges, Solutions and Trends”的学术报告。
摘要：For around a decade now, deep learning has revolutionised computer vision research. However, some key questions remain unanswered: 1. Why do deep-learning networks require extremely high dimensions to encode representational information while human vision does not? 2. Can convolutional neural networks effectively represent image/video data? 3. How can multimodal data fusion be achieved in deep networks? 4. How can machines learn from a few annotated samples? In this talk, I will discuss our team's efforts to address these questions, highlighting progress and future directions at the intersection of deep learning and computer vision.
报告人介绍: 韩军功，英国谢菲尔德大学（红砖大学，6名诺奖获得者）计算机学院讲席教授、计算机视觉团队负责人、任英国华威大学荣誉教授。韩军功及其团队在多媒体内容分析、多模态视觉感知、机器学习等研究领域贡献了多个原创性工作，共发表IEEE/ACM Trans 论文超过100篇，CCF A 类会议论文70篇，连年入选斯坦福大学全球前2%顶尖科学家榜单，Google Scholar总引用19200余次，H-指数70。任5个本领域著名杂志（3个IEEE Transactions）的执行主编和副主编。获批欧盟、美国专利各1项；3项技术实现商业化；其中1项获国际工业奖项。任国际模式识别协会会士、亚太地区人工智能协会会士。
