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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 21 - 40 of 277 [Previous]  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU, IBISML, IPSJ-CVIM [detail] 2023-03-02
11:05
Hokkaido Future University Hakodate
(Primary: On-site, Secondary: Online)
On the Effectiveness of Formula-Driven Supervised Learning for Medical Image Tasks
Ryuto Endo, Shuya Takahashi, Eisaku Maeda (TDU) PRMU2022-71 IBISML2022-78
Deep learning for image information processing often uses manually maintained natural image data. However, these data ha... [more] PRMU2022-71 IBISML2022-78
pp.71-75
PRMU, IBISML, IPSJ-CVIM [detail] 2023-03-02
17:00
Hokkaido Future University Hakodate
(Primary: On-site, Secondary: Online)
A Semi-Supervised Learning Framework for Handwritten Text Recognition using Mixed Augmentations and Scheduled Pseudo-Label Loss
Masayuki Honda, Hung Tuan Nguyen, Cuong Tuan Nguyen (TUAT), Cong Kha Nguyen, Ryosuke Odate, Takashi Kanemaru (Hitachi Ltd.), Masaki Nakagawa (TUAT) PRMU2022-97 IBISML2022-104
We propose Incremental Teacher Model, a semi-supervised learning (SSL) framework for handwriting text recognition. The f... [more] PRMU2022-97 IBISML2022-104
pp.199-204
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] 2023-02-28
17:15
Okinawa
(Primary: On-site, Secondary: Online)
DNN-based Noise Reduction Using Noise Signal for Target Signal
Ryota Hiromasa, Hien Ohnaka, Ryoichi Miyazaki (NITTC) EA2022-93 SIP2022-137 SP2022-57
This study proposes a DNN-based noise reduction method that uses noise signals instead of clean speech signals as the ta... [more] EA2022-93 SIP2022-137 SP2022-57
pp.101-106
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
11:00
Okinawa
(Primary: On-site, Secondary: Online)
Analysis of Noisy-target Training for DNN-based speech enhancement and investigation towards its practical use
Takuya Fujimura, Tomoki Toda (Nagoya Univ.) EA2022-112 SIP2022-156 SP2022-76
Deep neural network (DNN)-based speech enhancement usually uses a clean speech as a training target. However, it is hard... [more] EA2022-112 SIP2022-156 SP2022-76
pp.221-226
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] 2023-02-21
10:30
Hokkaido Hokkaido Univ. Improving Fashion Compatibility Prediction with Color Distortion Prediction
Ling Xiao, Toshihiko Yamasaki (UTokyo) ITS2022-44 IE2022-61
Fashion compatibility prediction is suffering from the fact that the labeled dataset may become outdated quickly due to ... [more] ITS2022-44 IE2022-61
pp.17-18
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
IBISML 2022-12-22
15:30
Kyoto Kyoto University
(Primary: On-site, Secondary: Online)
[Short Paper] Semi supervised image classification using unreliable pseudo label
Jihong Hu, Yinhao Li, Yen-Wei Chen (Ritsumeikan Univ.) IBISML2022-47
Semi-supervised learning (SSL), which automatically annotates unlabeled data with pseudo labels during training, has ach... [more] IBISML2022-47
pp.24-29
IBISML 2022-12-23
11:10
Kyoto Kyoto University
(Primary: On-site, Secondary: Online)
Enhancement of Audio Signals Using Learning from Positive and Unlabelled Data
Nobutaka Ito, Masashi Sugiyama (UTokyo) IBISML2022-56
Audio signal enhancement (SE) is the task of extracting a desired class of sounds (a “signal”) from an observed sound mi... [more] IBISML2022-56
pp.94-100
RCS, NS
(Joint)
2022-12-16
10:45
Aichi Nagoya Institute of Technology, and Online
(Primary: On-site, Secondary: Online)
[Encouragement Talk] A study on CSI-based Human Detection System Using Semi-Supervised Machine Learning
Naoki Osumi, Kosuke Tsuji, Ryotaro Isshiki, Yuhei Nagao, Leonardo Lanante, Masayuki Kurosaki, Hiroshi Ochi (Kyutech) RCS2022-201
In recent years, research on CSI (Channel State Information) based wireless sensing using wireless LAN has been gatherin... [more] RCS2022-201
pp.87-92
PRMU 2022-12-15
15:30
Toyama Toyama International Conference Center
(Primary: On-site, Secondary: Online)
Training Method for Image-based Instance Segmentation by Video-based Object-Centric Representation Learning
Tomokazu Kaneko, Ryosuke Sakai, Soma Shiraishi (NEC) PRMU2022-40
Object-centric representation learning (OCRL) aims to separate and extract object-wise representations from an image.
... [more]
PRMU2022-40
pp.43-48
NLC, IPSJ-NL, SP, IPSJ-SLP [detail] 2022-11-30
15:30
Tokyo
(Primary: On-site, Secondary: Online)
Semi-supervised joint training of text to speech and automatic speech recognition using unpaired text data
Naoki Makishima, Satoshi Suzuki, Atsushi Ando, Ryo Masumura (NTT) NLC2022-14 SP2022-34
This paper presents a novel joint training of text to speech (TTS) and automatic speech recognition (ASR) with small amo... [more] NLC2022-14 SP2022-34
pp.27-32
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
SWIM 2022-11-26
15:40
Tokyo Kikai-Shinko-Kaikan Bldg.
(Primary: On-site, Secondary: Online)
Sample Program Recommendation System to Support Programming Education
Yoshihisa Udagawa (Tokyo Univ. of Information Sciences) SWIM2022-24
One effective way to learn programming techniques is to reuse sample programs. As the number of sample programs increase... [more] SWIM2022-24
pp.20-26
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
SIS, ITE-BCT 2022-10-14
10:00
Aomori Hachinohe Institute of Technology
(Primary: On-site, Secondary: Online)
Robust Semi-Supervised Learning for Noisy Labels Using Early-learning Regularization and Weighted Loss
Ryota Higashimoto, Soh Yoshida, Mitsuji Muneyasu (Kansai Univ.) SIS2022-16
Training Deep Neural Networks (DNNs) on datasets with incorrect labels (label noise) is an important challenge. In the p... [more] SIS2022-16
pp.27-32
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
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