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| 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
16:45 |
Online |
online |
A Note on Disentanglement Using Deep Generative Model Based on Variational Autoencoder
-- Introduction of Regularization Losses Based on Metrics of Disentangled Representation --
Nao Nakagawa, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we study disentangled representation learning using a deep generative model based on Variational Autoenco... [more] |
MMS2022-19 ME2022-44 AIT2022-19
pp.97-102 |
| HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2020-02-27
14:55 |
Hokkaido |
Hokkaido Univ.
(Cancelled) |
A Note on Estimation of Image Categories Using Brain Activity While Viewing Images Based on MVBGM-MS
Yusuke Akamatsu (Hokkaido Univ.), Ryosuke Harakawa (Nagaoka Univ. of Tech.), Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents multi-view Bayesian generative model for multi-subject fMRI data (MVBGM-MS) for accurate estimation ... [more] |
MMS2020-16 HI2020-16 ME2020-44 AIT2020-16
pp.79-83 |
| HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2020-02-28
15:10 |
Hokkaido |
Hokkaido Univ.
(Cancelled) |
Unpaired Learning for Noise-free, Scale Invariant, and Interpretable Image Enhancement
Satoshi Kosugi, Toshihiko Yamasaki (Univ. of Tokyo) |
This paper tackles unpaired image enhancement, a task of learning a mapping function which transforms input images into ... [more] |
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