您现在的位置:网站首页>通知公告

通知公告

【生医学术讲座】--Learning the relationship between neighboring pixels for some vision tasks

文章来源: 作者: 发布时间:2020年01月02日 点击数: 字体:

主讲嘉宾:许永超 副教授

时  间: 2020年01月08日下午16:00-17:30

地  点:澳彩彩票官方网站西丽校区A2-517会议室

主 持 人:雷柏英 副教授

主讲嘉宾简介:

永超,男,博士,2013得法国巴黎大博士学会,中科技大学信学院副教授,博士生导师,楚天学子,2018年依托中国形学学会入中国科青年托人才划,回国前任于巴黎高等信息工程学院Tenured Assistant Professor,研究域涉及数学形学、景文字检测识别、医学像分析、算机视觉。在包括《IEEE Trans. PAMI》、《IEEE Trans. IP》、CVPR、ICCV等重要国期刊和会议发表学生文 40余 篇,其中一作TPAMI两篇。现任中国图象图形学学会CSIG青年工作委员会通讯委员,CSIG图象视频通信专委会通讯委员

报告简介(Abstract):

The relationship between neighboring pixels plays an important role in many vision applications. A typical example of a relationship between neighboring pixels is the intensity order, which gives rise to some morphological tree-based image representations (e.g., Min/Max tree and tree of shapes). These trees have been shown useful for many applications, ranging from image filtering to object detection and segmentation. Yet, these intensity order based trees do not always perform well for analyzing complex natural images.  The success of deep learning in many vision tasks motivates us to resort to convolutional neural networks (CNNs) for learning such a relationship instead of relying on the simple intensity order.  As a starting point, we propose the flux or direction field representation that encodes the relationship between neighboring pixels. We then leverage CNNs to learn such a representation and develop some customized post-processings for several vision tasks, such as symmetry detection, scene text detection, generic image segmentation, and crowd counting by localization.