We are pleased to announce that Satoshi Tsutsui, a PhD candidate at Indiana University in USA, will give a talk about computer vision, especially about computer vision with limited labeled data. You are all invited. Registration in advance is required. #codh9
|Title||Computer Vision with Limited Labeled Data|
|Date||16:30-17:30, January 8 (Tue), 2019|
|Venue||1208 Meeting Room (12F), National Institute of Informatics. Access to NII.|
|Abstract||Computer vision is making remarkable progress these days supported by deep learning. Deep leaning requires huge amount of training data, but the cost to annotate many images is often high. Various approaches have been proposed to circumvent this problem such as transfer learning, semi-supervised learning, data argumentation, and training data synthesis, but the best strategy depends on the specific application. This talk discusses several case studies on computer vision with limited labeled data. The examples include scientific figure detection, drivable space segmentation for self-driving cars, anatomical segmentation for pelvic magnetic resonance images, nail detection for nail disease images, and children's visual learning analysis with head-mounted camera.|
|Bio||Satoshi Tsutsui is a PhD candidate at Indiana University in USA, advised by David Crandall. He is interested in computer vision, deep learning, and their applications. In the past, he interned at Peking University in China where he worked on computer vision for medical applications, and at Preferred Networks in Japan where he worked on computer vision for autonomous driving. Detail: http://homes.sice.indiana.edu/stsutsui/.|
You are all invited, free of charge. Registration in advance is required using the following form.