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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| ITE-ME, ITE-IST, BioX, SIP, MI, 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)  SIP2024-5 BioX2024-5 IE2024-5 MI2024-5 |
Deep learning has been shown to be effective in decoding the content of a speaker's speech from recordings of brain acti... [more] | SIP2024-5 BioX2024-5 IE2024-5 MI2024-5 pp.23-28 |
| MI | 2024-03-04 15:58 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Representations obtained by self-supervised learning of hierarchical ViT to discriminate between benign and malignant breast tumors Akiomi Ishikawa (NIT), Kouji Arihiro (HIrosima Univ), Hidekata Hontani (NIT) MI2023-88 |
In this paper, I report a method to apply the representation of pathological microscopic images obtained by self-supervi... [more] | MI2023-88 pp.184-185 |
| SP, NLC, IPSJ-SLP, IPSJ-NL [detail] | 2023-12-03 11:05 |
Tokyo | Kikai-Shinko-Kaikan Bldg. (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Self-supervised learning model based emotion transfer and intensity control technology for expressive speech synthesis Wei Li, Nobuaki Minematsu, Daisuke Saito (Univ. of Tokyo) NLC2023-21 SP2023-41 |
Emotion transfer techniques, which transfersba the speaking style from the reference speech to the target speech, are wi... [more] | NLC2023-21 SP2023-41 pp.43-48 |
| BioX | 2023-10-13 10:20 |
Okinawa | Nobumoto Ohama Memorial Hall | Discrimination between Real and Generated Gestures of Speakers
-- An Attempt to Improve Generalization Performance in Unseen Generation Methods through Self-Supervised Learning -- Geng Mu (AGU), Naoshi Kaneko (TDU), Kazuhiko Sumi (AGU) BioX2023-67 |
Currently, discerning artificially generated misinformation is a critical societal challenge, with research progressing ... [more] | BioX2023-67 pp.44-49 |
| IBISML | 2023-09-08 13:25 |
Osaka | Osaka Metropolitan University (Nakamozu Campus) (Primary: On-site, Secondary: Online) |
Consideration of Negative Samples in Contrastive Learning Daiki Ishiguro, Tomoko Ozeki (Tokai Univ.) IBISML2023-28 |
Contrastive learning has achieved accuracy comparable to supervised learning. In this method, the transformed image pair... [more] | IBISML2023-28 pp.16-21 |
| MI | 2023-03-06 17:04 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Rotation-Equivariant CNN for Medical Image Processing Applications Ryota Ogino, Kugler Mauricio, Tatsuya Yokota, Hidekata Hontani (NITech) MI2022-96 |
In this study, we report an attempt to use a Rotation-Equivariant CNN to organize image data whose rotation direction an... [more] | MI2022-96 pp.113-114 |
| MI | 2023-03-07 15:38 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
A Denoising Method for Low Dose CT by Iterative Processing Using Self-Supervised Learning Yuki Sato, Hiroyuki Kudo (Univ of Tsukuba) MI2022-121 |
In recent years, patient exposure has become an issue, and low-dose CT, which reduces the amount of radiation irradiated... [more] | MI2022-121 pp.192-193 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-02-28 15:55 |
Okinawa | (Primary: On-site, Secondary: Online) |
Self-Supervised Learning With Spatial Audio-Visual Recording for Sound Event Localization and Detection Yoto Fujita (Kyoto Univ.), Yoshiaki Bando (AIST), Keisuke Imoto (Doshisha Univ./AIST), Masaki Onihsi (AIST), Yoshii Kazuyoshi (Kyoto Univ.) EA2022-89 SIP2022-133 SP2022-53 |
This paper describes an unsupervised pre-training method for sound event localization and detection (SELD) on multi-chan... [more] | EA2022-89 SIP2022-133 SP2022-53 pp.78-82 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-03-01 09:50 |
Okinawa | (Primary: On-site, Secondary: Online) |
Domain Adaptation for Improving End-to-end ASR Performance of Classroom Speech with Variable Recording Condition Raufun Nahar, Rino Suzuki, Atsuhiko Kai (Shizuoka Univ.) EA2022-101 SIP2022-145 SP2022-65 |
Automatic speech recognition (ASR) of real-world speech recorded in real environment has been a challenge in the field o... [more] | EA2022-101 SIP2022-145 SP2022-65 pp.153-158 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-03-01 15:50 |
Okinawa | (Primary: On-site, Secondary: Online) |
The linguistic influence on speaker verification based on Self-Supervised Learning Tomoka Wakamatsu (Tokyo Metropolitan Univ.), Atsushi Ando (NTT), Sayaka Shiota (Tokyo Metropolitan Univ.), Ryo Masumura (NTT), Hitoshi Kiya (Tokyo Metropolitan Univ.) EA2022-118 SIP2022-162 SP2022-82 |
In recent years, statistical models utilizing Self-Supervised Learning (SSL) have been employed in various fields It ha... [more] |
EA2022-118 SIP2022-162 SP2022-82 pp.247-252 |
| IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2023-02-22 10:00 |
Hokkaido | Hokkaido Univ. | ITS2022-60 IE2022-77 |
Unsupervised domain adaptation (UDA) is extremely effective for transferring knowledge from a label-rich source domain t... [more] | ITS2022-60 IE2022-77 pp.101-106 |
| NLC, IPSJ-NL, SP, IPSJ-SLP [detail] | 2022-12-01 15:20 |
Tokyo | (Primary: On-site, Secondary: Online) |
Domain and language adaptation of large-scale pretrained model for speech recognition of low-resource language Kak Soky (Kyoto University), Sheng Li (NICT), Chenhui Chu, Tatsuya Kawahara (Kyoto University) NLC2022-17 SP2022-37 |
The self-supervised learning (SSL) models are effective for automatic speech recognition (ASR). Due to the huge paramete... [more] | NLC2022-17 SP2022-37 pp.45-49 |
| CAS, MSS, IPSJ-AL [detail] | 2022-11-18 14:05 |
Kochi | (Primary: On-site, Secondary: Online) |
Unsupervised Representation Learning over Decentralized Federated Learning Haruki Sakurai, Hideya Ochiai, Hiroshi Esaki (Univ. Tokyo) CAS2022-54 MSS2022-37 |
Contrastive Learning is a form of self-supervised learning, a method for learning a general-purpose encoder using a larg... [more] | CAS2022-54 MSS2022-37 pp.79-82 |
| MVE | 2022-09-09 10:30 |
Tokyo | (Primary: On-site, Secondary: Online) |
Self-Supervised Learning for Echo Chamber-aware Friend Recommendation Luwei Zhang, Toshihiko Yamsaski (UTokyo) MVE2022-14 |
In recommender systems, the creation of echo chambers and filter bubbles obviously lowers the diversity of recommendatio... [more] | MVE2022-14 pp.22-25 |
| SIP | 2022-08-25 14:33 |
Okinawa | Nobumoto Ohama Memorial Hall (Ishigaki Island) (Primary: On-site, Secondary: Online) |
Structured Deep Image Prior with Interscale Thresholding Jikai Li, Shogo Muramatsu (Niigata Univ.) SIP2022-55 |
This work proposes a novel image denoising technique inspired by the deep image prior (DIP) method. Our contribution is ... [more] | SIP2022-55 pp.31-36 |
| SIP | 2022-08-26 15:33 |
Okinawa | Nobumoto Ohama Memorial Hall (Ishigaki Island) (Primary: On-site, Secondary: Online) |
Locally-Structured Unitary Network to Capture Tangent Spaces of Manifold Godage Yasas, Shogo Muramatsu (Niigata Univ.) SIP2022-75 |
This work proposes a unique linear transform, locally-structured unitary network (LSUN), that captures tangent spaces of... [more] | SIP2022-75 pp.129-133 |
| PRMU, IPSJ-CVIM | 2022-03-11 17:10 |
Online | Online | PRMU2021-90 |
No English abstract [more] | PRMU2021-90 pp.186-191 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-21 13:30 |
Online | Online | A Note on Automatic Diagnosis of Helicobacter Pylori Infection Based on Self-Supervised Learning and Self-Knowledge Distillation Guang Li, Ren Togo (Hokkaido Univ.), Katsuhiro Mabe (Junpukai Health Maintenance Center), Shunpei Nishida (Olympus), Yoshihiro Tomoda (Olympus Medical Systems), Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper proposes a novel method for automatic diagnosis of Helicobacter pylori (H. pylori) infection based on self-su... [more] | |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-22 10:00 |
Online | Online | Pretext-Contrastive Learning for Self-Supervised Video Feature Learning Li Tao (UTokyo), Xueting Wang (CyberAgent, Inc.), Toshihiko Yamasaki (UTokyo) ITS2021-43 IE2021-52 |
Recently, pretext task-based methods are proposed one after another in self-supervised video feature learning. Contrasti... [more] | ITS2021-43 IE2021-52 pp.109-114 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-22 10:45 |
Online | Online | ITS2021-46 IE2021-55 |
There has been a tremendous progress in unsupervised domain adaptation (UDA), which aims to transfer knowledge acquired ... [more] | ITS2021-46 IE2021-55 pp.127-132 |
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