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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NC, MBE (Joint) |
2024-03-12 13:55 |
Tokyo | The Univ. of Tokyo (Primary: On-site, Secondary: Online) |
Identification of filamentous fungi by segmentation models using consistency regularization and classmix Taiga Shimizu (Yamanashi Univ.), Waleed Asghar (Oklahoma State Univ.), Ryota Kataoka, Motonobu Hattori (Yamanashi Univ.)  NC2023-57 |
In agriculture, soil diagnosis is necessary to protect the environment. However, since current diagnostic methods are no... [more] | NC2023-57 pp.81-86 |
| PRMU, IPSJ-CVIM, IPSJ-DCC, IPSJ-CGVI | 2023-11-16 15:10 |
Tottori | (Primary: On-site, Secondary: Online) |
Pseudo-label selection for medical images Takehiro Yamane (Kyushu Univ.), Itaru Tsuge, Susumu Saito (Kyoto Univ.), Ryoma Bise (Kyushu Univ.) PRMU2023-17 |
(To be available after the conference date) [more] | PRMU2023-17 pp.11-15 |
| NLP, MSS | 2023-03-17 16:05 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Lightweighting Noisy Student Semi-Supervised Learning by Applying MobileNet Yuga Morishima, Hidehiro Nakano (Tokyo City Univ.) MSS2022-108 NLP2022-153 |
Recently, Convolutional Neural Networks (CNNs) have attracted much attention in various fields such as image classificat... [more] | MSS2022-108 NLP2022-153 pp.220-224 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-03 16:10 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Sota Kato, Kazuhiro Hotta (Meijo Univ.) PRMU2022-110 IBISML2022-117 |
(To be available after the conference date) [more] | PRMU2022-110 IBISML2022-117 pp.269-274 |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-03-01 09:10 |
Okinawa | (Primary: On-site, Secondary: Online) |
Joint analysis of acoustic scenes and sound events based on semi-supervised learning Ami Igarashi, Shunsuke Tsubaki, Keisuke Imoto (DU) EA2022-103 SIP2022-147 SP2022-67 |
(To be available after the conference date) [more] | EA2022-103 SIP2022-147 SP2022-67 pp.165-170 |
| 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 |
| 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 |
| 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 |
| CS | 2022-07-14 10:20 |
Kagoshima | Yakushima Environmental and Cultural Village Center (Primary: On-site, Secondary: Online) |
User Data Selection using CNN-Feature Extractor for Fingerprint Localization Yohei Konishi, Satoru Aikawa, Shinichiro Yamamoto (Univ of Hyogo) CS2022-10 |
(To be available after the conference date) [more] | CS2022-10 pp.1-2 |
| CCS, NLP | 2022-06-09 14:15 |
Osaka | (Primary: On-site, Secondary: Online) |
Improvement of Recognition Accuracy by Sequential Execution of Unsupervised Learning and Semi-supervised Learning Hiroki Murakami, Hidehiro Nakano (Tokyo City Univ.) NLP2022-4 CCS2022-4 |
In this study, we propose a sequential learning method that improves recognition accuracy by alternately utilizing the k... [more] | NLP2022-4 CCS2022-4 pp.17-22 |
| SIS, IPSJ-AVM | 2022-06-09 15:00 |
Fukuoka | KIT(Wakamatsu Campus) (Primary: On-site, Secondary: Online) |
[Invited Talk]
Advanced applications of machine learning techniques towards high-performance and cost-effective visual inspection AI Terumasa Tokunaga (Kyutech) SIS2022-6 |
Visual inspection is an essential step for quality control in manufacturing. Recently, many researchers have shown great... [more] | SIS2022-6 p.30 |
| SeMI | 2022-01-20 15:00 |
Nagano | (Primary: On-site, Secondary: Online) |
[Short Paper]
Evaluation of Few Round Training with Distillation-Based Semi-Supervised Federated Learning Yuki Yoshida (Tokyo Tech), Sohei Itahara (Kyoto Univ.), Takayuki Nishio (Tokyo Tech) SeMI2021-65 |
This paper studies how to reduce the number of rounds in model training using Distillation-based Semi-supervised federat... [more] | SeMI2021-65 pp.48-50 |
| CS | 2021-10-15 10:40 |
Online | Online | User Data Selection using CNN Feature Extractor for Fingerprint Localization Yohei Konishi, Satoru Aikawa, Shinichiro Yamamoto, Yuta Sakai (Univ of Hyogo) CS2021-57 |
This paper scopes a method that applies CNN to Fingerprint indoor localization. AP information are used to train the CNN... [more] | CS2021-57 pp.26-31 |
| RCS, SR, NS, SeMI, RCC (Joint) |
2021-07-16 09:00 |
Online | Online | A Study on Automatic Labeling MethodUsing Semi-Supervised Learning for Wireless LAN Sensing Naoki Osumi, Kosuke Tsuji, Ryotaro Isshiki, Yuhei Nagao, Leonardo Lanante, Masayuki Kurosaki, Hiroshi Ochi (Kyutech) RCS2021-93 |
In recent years, research on CSI (Channel State Information) based wireless sensing using wireless LAN has been gatherin... [more] | RCS2021-93 pp.74-79 |
| PRMU, IPSJ-CVIM | 2021-03-04 10:15 |
Online | Online | Semi-supervised temporal image sequence generation conditioned on non-visual sensor signals Kawakami Sota, Kei Okada, Naoko Nitta, Kazuaki Nakamura, Noboru Babaguchi (Osaka Univ.) PRMU2020-72 |
(To be available after the conference date) [more] | PRMU2020-72 pp.19-24 |
| EA, US, SP, SIP, IPSJ-SLP [detail] | 2021-03-04 09:00 |
Online | Online | Anomalous Sound Detection Using a Binary Classification Model Considering Class Centroids Ibuki Kuroyanagi, Tomiki Hayashi, Kazuya Takeda, Tomoki Toda (Nagoya Univ) EA2020-79 SIP2020-110 SP2020-44 |
In an anomalous sound detection system, it is necessary to detect unknown anomalous sounds using only normal sound data.... [more] | EA2020-79 SIP2020-110 SP2020-44 pp.114-121 |
| IBISML | 2020-10-20 10:50 |
Online | Online | System operation for estimation of road condition using tire vibration data Satoru Kawamata (Bridgestone), Tomoko Matsui (ISM), Mitsuhiro Nishida, Takeshi Masago (Bridgestone) IBISML2020-10 |
In a system that estimates the road surface condition from tire sensor data and supports safe driving, it is crucial to ... [more] | IBISML2020-10 pp.14-19 |
| EST | 2020-01-30 09:40 |
Oita | Beppu International Convention Center | Embedded object identification from ground penetrating radar image by semi-supervised learning using variational auto-encoder Tomoyuki Kimoto (NIT, Oita), Jun Sonoda (NIT, Sendai) EST2019-80 |
Recently, deterioration of social infrastructures such as tunnels and bridges becomes serious social problem. It is requ... [more] | EST2019-80 pp.7-12 |
| SeMI | 2020-01-31 10:00 |
Kagawa | [Poster Presentation]
Communication-Efficient Federated Learning Using Non-Labeled Data Souhei Itahara, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto (Kyoto Univ) SeMI2019-109 |
Federated learning (FL) is a machine learning setting where many mobile devices collaboratively train a machine learning... [more] | SeMI2019-109 pp.47-48 |
|
| PRMU | 2019-12-19 13:30 |
Oita | PRMU2019-50 |
We propose a new problem setting and method that uses cancer type ratio as weak supervision for semi-supervised learning... [more] | PRMU2019-50 pp.23-27 |
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