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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 # |
| ME, IST, IEICE-BioX, IEICE-SIP, IEICE-MI, IEICE-IE [detail] |
2024-06-07
09:30 |
Niigata |
Nigata University (Ekinan-Campus "TOKIMATE") |
A pre-trained representation learning model can be used to decode speech from intracranial recordings
Shoya Murakami, Shuji Komeiji, Kai Shigemi (TUAT), Takumi Mitsuhashi, Yasushi Iimura, Hiroharu Suzuki, Hidenori Sugano (Juntendo Univ.), Koichi Shinoda (Tokyo Tech), Toshihisa Tanaka (TUAT) |
Deep learning has been shown to be effective in decoding the content of a speaker's speech from recordings of brain acti... [more] |
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| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-22
15:20 |
Online |
online |
A Note on Perceived Visual Content Estimation Based on Compressed Reconstruction Network Using Brain Signals While Gazing on Images
Takaaki Higashi, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido University) |
In this paper, we propose a method to reconstruct a perceived image using brain signals obtained during gazing images. S... [more] |
MMS2022-28 ME2022-53 AIT2022-28
pp.349-353 |
| IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2021-02-18
13:25 |
Online |
Online |
A Note on Estimation of Semantic Content Based on a Question Answering Model Using Brain Activity Data while Viewing Images
-- Improvement of Estimation Performance Based on Fine-tuning of the VQA model --
Saya Takada, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we propose a semantic content estimation method based on a question and answer generation model using bra... [more] |
MMS2021-6 ME2021-6 AIT2021-6
pp.27-31 |
| 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 |
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