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Search Results: Conference Papers
 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 213  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
RCS, NS
(Joint)
2022-12-15
- 2022-12-16
Aichi Nagoya Institute of Technology, and Online
(Primary: On-site, Secondary: Online)
[Encouragement Talk] 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)
(To be available after the conference date) [more]
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
(To be available after the conference date) [more] SIS2022-16
pp.27-32
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
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
MI 2022-07-08
17:00
Hokkaido
(Primary: On-site, Secondary: Online)
[Short Paper] Weakly-Supervised Focal Liver Lesion Detection in CT Images
He Li, Yutaro Iwamoto (Ritsumeikan Univ.), Xianhua Han (Yamaguchi Univ.), Lanfen Lin, Ruofeng Tong, Hongjie Hu (Zhejiang Univ.), Akira Furukawa (Tokyo Metropolitan Univ.), Shuzo Kanasaki (Koseikai Takeda Hospital), Yen-Wei Chen (Ritsumeikan Univ.) MI2022-40
Convolutional neural networks have been widely used for anomaly detection and one of their most common methods is autoen... [more] MI2022-40
pp.30-33
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
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, 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
MSS, NLP 2022-03-29
09:40
Online Online Effects of sparse connections in spiking neural networks for unsupervised pattern recognition
Hiroki Shinagawa, Kantaro Fujiwara, Gouhei Tanaka (Univ. of Tokyo) MSS2021-69 NLP2021-140
Recently, the spiking neural network (SNN) models, which compute using spatio-temporal information representation by neu... [more] MSS2021-69 NLP2021-140
pp.71-76
PRMU, IPSJ-CVIM 2022-03-11
17:10
Online Online PRMU2021-90 No English abstract [more] PRMU2021-90
pp.186-191
CQ, IMQ, MVE, IE
(Joint) [detail]
2022-03-09
09:45
Online Online (Zoom) Improving Weakly Supervised Instance Segmentation by Encoding Motion Information via Optical Flow
Jun Ikeda, Junichiro Mori (UT) IMQ2021-15 IE2021-77 MVE2021-44
Weakly supervised instance segmentation is an important task that can significantly reduce the annotation cost of model ... [more] IMQ2021-15 IE2021-77 MVE2021-44
pp.27-32
SS 2022-03-07
11:20
Online Online Trace Ablation and Fault Localization per Method Using Machine Learning Models for Automatic Classification of Test Execution Results
Takuma Ikeda, Kozo Okano, Shinpei Ogata (Shinshu Univ.), Shin Nakajima (NII) SS2021-44
The problem to solve automatically classifying the results of test executions is called the test oracle problem. This is... [more] SS2021-44
pp.13-18
MW 2022-03-04
11:10
Online Online Deep-Learning Based Anomaly Detection Method for Microwave Non-destructive Road Monitoring
Takahide Morooka, Shouhei Kidera (Univ. of Electro-Communications) MW2021-134
Microwave radar is promising as large-scale and speedy non-destructive monitoring tool for aging road or tunnel because ... [more] MW2021-134
pp.128-133
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] 2022-02-21
11:30
Online Online ITS2021-28 IE2021-37 The dynamic range of electronic imaging is orders of magnitudes smaller than that of human vision. To obtain images of h... [more] ITS2021-28 IE2021-37
pp.19-24
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
 Results 1 - 20 of 213  /  [Next]  
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