基于美国有线电视新闻网的大规模图像数据联合聚类与表示学习
CNN-Based Joint Clustering and Representation Learning for Large-Scale Image Data
林嘉文   Chia-wen Lin
报告人照片   Prof. Chia-Wen Lin received his PhD degree in Electrical Engineering from National Tsing Hua University (NTHU), Hsinchu, Taiwan in 2000. He is currently a Professor with the Department of Electrical Engineering, National Tsing Hua University, Taiwan. He is Deputy Director of the AI Research Center of NTHU and Director of the Multimedia Technology Research Center of the EECS College, NTHU. Dr. Lin is an IEEE Fellow.
  Given a large unlabeled set of images, how to efficiently and effectively group them into clusters based on extracted visual representations remains a challenging problem. To address this problem, we propose a convolutional neural network (CNN) to jointly solve clustering and representation learning in an iterative manner. We also propose a feature drift compensation scheme to mitigate the drift error caused by feature mismatch in representation learning. Experimental results demonstrate the proposed method outperforms start-of-the-art clustering schemes in terms of accuracy and storage complexity on large-scale image sets containing millions of images.
报告时间:2018年01月15日09时00分    报告地点:西区科技西楼1213会议室
报名截止日期:2018年01月15日    可选人数:50