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All Technical Committee Conferences (Searched in: Recent 10 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 # |
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
13:00 |
Online |
online |
Domain Incremental Leaning with Adaptive Loss Functions
Takumi Kawashima (UTokyo), Go Irie, Daiki Ikami (NTT), Kiyoharu Aizawa (UTokyo) |
During domain incremental learning of image classification task, the distribution of images continually change, and mode... [more] |
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| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-22
10:45 |
Online |
online |
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There has been a tremendous progress in unsupervised domain adaptation (UDA), which aims to transfer knowledge acquired ... [more] |
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| HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2020-02-27
14:15 |
Hokkaido |
Hokkaido Univ.
(Cancelled) |
Translation from Line Drawings to Manga Using Deep Learning by Adding a Screentone Layer
Koki Tsubota, Daiki Ikami, Kiyoharu Aizawa (UTokyo) |
The translation from line drawings to manga is one of the processes for creating manga and the automation of this proces... [more] |
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| ME, IEICE-IE, IEICE-ITS, MMS, HI, AIT [detail] |
2019-02-19
14:45 |
Hokkaido |
Hokkaido Univ. |
Data Augmentation via Transformer and Generating Diverse QA Pairs for Visual Question Answering
Masao Tsukiyama, Daiki Ikami (Tokyo Univ.), Go Irie (NTT), Kiyoharu Aizawa (Tokyo Univ.) |
[more] |
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| IEICE-ITS, IEICE-IE, MMS, HI, ME, AIT [detail] |
2018-02-16
10:45 |
Hokkaido |
Hokkaido Univ. |
Parallel feature pooling without information loss
Akito Takeki, Daiki Ikami (Univ. Tokyo), Go Irie (NTT), Kiyoharu Aizawa (Univ. Tokyo) |
[more] |
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| CE, MMS, AIT, HI, ME, IEICE-ITS, IEICE-IE [detail] |
2017-02-21
09:00 |
Hokkaido |
Hokkaido Univ. |
A Comparative Evaluation of Deep Features
-- Classifier-based Learning vs. Distance Metric Learning. --
Shota Horiguchi, Daiki Ikami, Kiyoharu Aizawa (UTokyo) |
The extraction of useful deep features is important for many computer vision tasks. Deep features extracted from classif... [more] |
MMS2017-35 CE2017-35 HI2017-35 ME2017-59 AIT2017-35
pp.199-204 |
| HI, IEICE-IE, AIT, IEICE-ITS, ME, MMS, CE [detail] |
2016-02-23
11:15 |
Hokkaido |
Hokudai |
Fast and Robust Relative Pose Estimation Based on Singular Values Minimization Problem
Daiki Ikami, Toshihiko Yamasaki, Kiyoharu Aizawa (UT) |
[more] |
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