Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
NLP, CCS |
2024-06-06 12:10 |
Fukuoka |
West Japan General Exhibition Center AIM |
Detection of Atrial Fibrillation from ECGs Using Unsupervised Learning Kentaro Sakai, Hiroyuki Kitajima (Kagawa Univ) |
(To be available after the conference date) [more] |
|
SeMI, IPSJ-ITS, IPSJ-MBL, IPSJ-DPS |
2024-05-17 09:00 |
Okinawa |
|
A basic study on human re-identification using 3D point cloud data focusing on body shape characteristics Shintaro Otsudo, Hiroaki Morino (SIT) SeMI2024-5 |
At indoor events, it is useful to be able to analyze the paths taken by people in order to design appropriate booth layo... [more] |
SeMI2024-5 pp.20-24 |
MI |
2024-03-03 17:18 |
Okinawa |
OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
3D shape reconstruction of colon with model-based unsupervised depth estimation Natsu Onozaka (Nagoya Univ.), Hayato Itoh (Fukuoka Univ.), Masahiro Oda (Nagoya Univ.), Masashi Misawa (Showa Univ.), Yuichi Mori (UiO), Shin-ei Kudo (Showa Univ.), Kensaku Mori (Nagoya Univ.) MI2023-60 |
We propose unsupervised trainig for the pose estimation in 3D reconstrcution of the colon from colonoscopic images by cl... [more] |
MI2023-60 pp.87-90 |
MI |
2024-03-04 09:00 |
Okinawa |
OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Distance-informed adversarial learning for metal artifact reduction Daisuke Shigemori, Megumi Nakao (Kyoto Univ.) MI2023-62 |
In this study, we propose an adversarial learning framework that utilises distance information from metal to reduce CT m... [more] |
MI2023-62 pp.95-98 |
NS, IN (Joint) |
2024-02-29 11:10 |
Okinawa |
Okinawa Convention Center |
An unsupervised online learning-based traffic classification and anomaly detection method for 5G-IIoT systems Yuxuan Shi, Qianqian Pan, Akihiro Nakao (U Tokyo) NS2023-188 |
In the context of Society 5.0, the evolution of the Internet of Things (IoT) and its ever growing demands of massive Mac... [more] |
NS2023-188 pp.96-102 |
DE, IPSJ-DBS |
2023-12-26 14:00 |
Tokyo |
Institute of Industrial Science, The University of Tokyo |
Interpretation of unsupervised clustering based on XAI Yu Sasaki, Fumiaki Saitoh (CIT) DE2023-28 |
Explainable Artificial Intelligence (XAI) aims to introduce transparency and interpretability into the decision-making o... [more] |
DE2023-28 pp.1-6 |
WIT, HI-SIGACI |
2023-12-07 11:15 |
Tokyo |
AIST Tokyo Waterfront (TBD) |
On Modeling Daily Activities of the Elderly Living Alone Using Markov Series of Dirichlet Multinomial Mixture Models Ken Sadohara (AIST) WIT2023-30 |
To develop smart home technology designed to analyze the activity of residents based on the logs of installed sensors, a... [more] |
WIT2023-30 pp.31-36 |
IA |
2023-09-22 10:40 |
Hokkaido |
Hokkaido Univeristy (Primary: On-site, Secondary: Online) |
OLIViS: An OSINT-Based Lightweight Method for Identifying Video Content Services for Capacity Planning in Backbone ISPs Yuki Tamura, Fumio Teraoka, Takao Kondo (Keio Univ.) IA2023-23 |
As of 2022, 66% of Internet traffic is generated by video content services, among which Netflix and YouTube are the domi... [more] |
IA2023-23 pp.75-82 |
PRMU, IPSJ-CVIM |
2023-05-19 15:40 |
Aichi |
(Primary: On-site, Secondary: Online) |
Object-Centric Representation Learning with Attention Mechanism Hidemoto Nakada, Hideki Asoh (AIST) PRMU2023-13 |
For object-centric representation learning, several slot-based methods, that separate objects using masks and learn the ... [more] |
PRMU2023-13 pp.68-73 |
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 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 |
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 |
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 |
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 |
SAT, RCS (Joint) |
2022-08-26 11:40 |
Hokkaido |
(Primary: On-site, Secondary: Online) |
Inter-cell Interference Control by Joint Transmit Power and Transmit Beamforming Control based on Machine Learning Naoto Tamada, Yuyuan Chang, Kazuhiko Fukawa (Tokyo Tech) RCS2022-118 |
In mobile communications, densely deployed small cell systems using the same frequency band are expected to increase the... [more] |
RCS2022-118 pp.120-125 |
AI |
2022-07-04 16:00 |
Hokkaido |
(Primary: On-site, Secondary: Online) |
Unsupervised Learning of a Dynamic Task Ordering Model for Crowdsourcing Ryo Yanagisawa (Waseda Univ.), Susumu Saito, Teppei Nakano (ifLab Inc.), Tetsunori Kobayashi, Tetsuji Ogawa (Waseda Univ.) AI2022-14 |
An unsupervised learning method for a dynamic task ordering model that optimizes the number of orders according to the d... [more] |
AI2022-14 pp.72-76 |
SP, IPSJ-MUS, IPSJ-SLP [detail] |
2022-06-17 15:00 |
Online |
Online |
SP2022-13 |
We investigate the method for unsupervised learning of artifacts correction networks used for post-processing of Multi B... [more] |
SP2022-13 pp.49-54 |
SP, IPSJ-MUS, IPSJ-SLP [detail] |
2022-06-18 15:00 |
Online |
Online |
Unsupervised Training of Sequential Neural Beamformer Using Blindly-separated and Non-separated Signals Kohei Saijo, Tetsuji Ogawa (Waseda Univ.) SP2022-25 |
We present an unsupervised training method of the sequential neural beamformer (Seq-NBF) using the separated signals fro... [more] |
SP2022-25 pp.110-115 |
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 |
SeMI, IPSJ-DPS, IPSJ-MBL, IPSJ-ITS |
2022-05-26 13:45 |
Okinawa |
(Primary: On-site, Secondary: Online) |
Unsupervised Learning-based Non-invasive Fetal ECG Signal Quality Assessment Xintong Shi, Kohei Yamamoto, Tomoaki Ohtsuki (Keio Univ.), Yutaka Matsui, Kazunari Owada (Atom Medical Co., Ltd.) SeMI2022-4 |
For fetal heart rate (FHR) monitoring, the non-invasive fetal electrocardiogram (FECG) obtained from abdomen surface ele... [more] |
SeMI2022-4 pp.15-19 |