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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
QIT (2nd) |
2023-12-17 17:30 |
Okinawa |
OIST (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Development of Scalable Telecom-Band Nanofiber Cavity QED Shinichi Sunami (NanoQT/Oxford), Jun Ikeda (Caltech/NanoQT), Ryotaro Inoue, Hideki Konishi, Shinya Kato, Akihisa Goban (NanoQT) |
[more] |
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CQ, IMQ, MVE, IE (Joint) [detail] |
2022-03-09 09:45 |
Online |
Online (Zoom) |
Improving Weakly Supervised Instance Segmentation by Encoding Motion Information via Optical Flow Jun Ikeda, Junichiro Mori (UT) IMQ2021-15 IE2021-77 MVE2021-44 |
Weakly supervised instance segmentation is an important task that can significantly reduce the annotation cost of model ... [more] |
IMQ2021-15 IE2021-77 MVE2021-44 pp.27-32 |
MVE |
2021-09-17 14:30 |
Online |
Online |
Improving Mask Generation Accuracy Exploiting Optical Flow in Weakly Supervised Instance Segmentation Jun Ikeda, Junichiro Mori (UTokyo) MVE2021-15 |
Weakly supervised instance segmentation is important because it reduces the huge pixel-level annotation cost required to... [more] |
MVE2021-15 pp.38-43 |
IE, IMQ, MVE, CQ (Joint) [detail] |
2020-03-05 09:45 |
Fukuoka |
Kyushu Institute of Technology (Cancelled but technical report was issued) |
Predicting the online video advertising effectiveness with multimodal deep learning Jun Ikeda, Hiroyuki Seshime, Xueting Wang, Toshihiko Yamasaki, Kiyoharu Aizawa (UTokyo) IMQ2019-41 IE2019-123 MVE2019-62 |
In this research, we propose a method for predicting the Click Through Rate of video ads and analyzing the factors that ... [more] |
IMQ2019-41 IE2019-123 MVE2019-62 pp.133-136 |
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