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
Computer Vision with Limited Labeled Data
16:30-17:30, January 8 (Tue), 2019
1208 Meeting Room (12F), National Institute of Informatics.
Access to NII.
Computer vision is making remarkable progress these days supported by deep learning. Deep learning 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.
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.
The seminar has fininshed. Thank you for your participation.
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DH 2022 Tokyo Commemorative Lecture Series / 17th CODH Seminar - Historical Big Data - THE DARK MATTER OF HISTORY
16th CODH Seminar - Digital Archives for Cities and Towns - Historical Big Data and Usage in the Real World
15th CODH Seminar - Art History Research to be Transformed by IIIF and AI - Interpreting Japanese Painting Scrolls in Middle Ages by Style Comparative Study on Large-Scale Facial Expression Data
14th CODH Seminar - 100 Recipes for IIIF Curation Platform
13th CODH Seminar - Present and Future of Historical Big Data Research
12th CODH Seminar (Online) - AI for Culture: From Japanese Art to Anime
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11th CODH Seminar - Text Mining for Analyzing Research Communities: Sociological Topics and Socio-Technical Imaginaries
10th CODH Seminar - Document Analysis and Character Recognition
9th CODH Seminar - Computer Vision with Limited Labeled Data
8th CODH Seminar - Exploring Deep Learning for Classical Japanese Literature, Machine Creativity, and Recurrent World Models!
7th CODH Seminar - Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer
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