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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MIKA (3rd) |
2023-10-10 15:35 |
Okinawa | Okinawa Jichikaikan (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Anomaly Detection using HDBSCAN and Deep SVDD Yusuke Noji, Tomotaka Kimura, Jun Cheng (Doshisha Univ.) |
In this presentation, we examine an anomaly detection method using Deep SVDD (Support Vector Data Description), a type o... [more] | |
| IA | 2023-09-22 14:00 |
Hokkaido | Hokkaido Univeristy (Primary: On-site, Secondary: Online) |
Investigation of Acoustic Feature Estimation Based on Periodicity of Mechanical Equipment for Remote Anomaly Detection System Rio Shigyo, Daiki Nobayashi, Kazuya Tsukamoto, Mitsunori Mizumachi, Takeshi Ikenaga (KIT)  IA2023-28 |
Status checks of mechanical equipment are typically being conducted by workers (manpower). However, since the check timi... [more] | IA2023-28 pp.105-108 |
| NS, IN, CS, NV (Joint) |
2023-09-08 09:30 |
Miyagi | Tohoku University (Primary: On-site, Secondary: Online) |
Network anomaly detection and failure scale estimation method Naoya Ogawa, Ryoichi Kawahara (Toyo Univ.) NS2023-57 |
In this paper, we propose a network anomaly detection and failure scale estimation method using AI. For anomaly detectio... [more] | NS2023-57 pp.32-37 |
| NS | 2023-04-14 11:40 |
Fukushima | Nihon University, Koriyama Campus + Online (Primary: On-site, Secondary: Online) |
Network Anomaly Detection through Variable Granularity Traffic Analysis Shohei Kamamura, Yuya Takeda (Seikei Univ.), Yuki Takei, Masato Nishiguchi, Yuhei Hayashi, Takayuki Fujiwara (NTT) NS2023-9 |
In the Society 5.0, it is important to accurately measure and analyze the communication traffic flow in wide-area IP net... [more] | NS2023-9 pp.44-49 |
| CCS | 2023-03-26 10:35 |
Hokkaido | RUSUTSU RESORT | Acquisition of physical kinetics of machines by reservoir computing Sena Kojima, Koki Minagawa, Taisei Saito, Tetsuya Asai (Hokkaido Univ.) CCS2022-67 |
This report focuses on an anomaly detection application of a machine’s dynamical system using reservoir computing. We pr... [more] | CCS2022-67 pp.25-30 |
| IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-15 11:00 |
Okinawa | Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
Evaluating the Efficiency of Anomaly Detection Methods for Temporal Networks Using the Graph Spectrum Masataka Nagao, Eriko Segawa, Yusuke Sakumoto (Kwansei Gakuin Univ.) CQ2022-83 |
LAD (Laplacian Anomaly Detection) is a method for detecting anomalies in dynamic networks using the eigenvalues (the gra... [more] | CQ2022-83 pp.19-24 |
| RCC, ISEC, IT, WBS | 2023-03-15 09:30 |
Yamaguchi | (Primary: On-site, Secondary: Online) |
Networks anomaly detection by VAE based on features extracted by CNN Higashihata Kazuki (Osaka Prefecture Univ.), Aoki Shigeki, Miyamoto Takao (Osaka Metropolitan Univ.) IT2022-111 ISEC2022-90 WBS2022-108 RCC2022-108 |
Anomaly-based IDS, one of the intrusion detection systems (IDS), can detect unknown anomalies, but there is a problem of... [more] | IT2022-111 ISEC2022-90 WBS2022-108 RCC2022-108 pp.269-276 |
| R | 2023-03-10 13:50 |
Hiroshima | (Primary: On-site, Secondary: Online) |
Failure Sign Detection by State Path Analysis for Fare Collection System
-- Evaluation by Sequential Pattern Mining with Mechatronics Knowledge -- Ken Ueno, Misato Ishikawa, Yuko Kobayashi, Takamitsu Sunaoshi (Toshiba), Kiyoku Endo (Toshiba Automation Systems Service) R2022-50 |
To detect failure sign on Fare Collection System (FCS) which has low failure rate accurately, we need the mechatronics k... [more] | R2022-50 pp.13-18 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 10:35 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Investigation of Appearance Inspection Method Considering the Number of Corresponding Local Patches Katsuhisa Kitaguchi, Yohei Nishizaki, Mamoru Saito (ORIST) PRMU2022-74 IBISML2022-81 |
There has been a great deal of research on appearance inspection using deep learning, which learns only from normal imag... [more] | PRMU2022-74 IBISML2022-81 pp.88-92 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-03 16:20 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Classifying Cable Tendency with Semantic Segmentation by Utilizing Real and Simulated RGB Data Pei-Chun Chien, Powei Liao, Eiji Fukuzawa, Jun Ohya (Waseda Univ.) PRMU2022-117 IBISML2022-124 |
Cable tendency is the potential shape or characteristic that a cable may possess while being manipulated during automate... [more] | PRMU2022-117 IBISML2022-124 pp.311-318 |
| IN, NS (Joint) |
2023-03-03 11:00 |
Okinawa | Okinawa Convention Centre + Online (Primary: On-site, Secondary: Online) |
Unidentified Floating Object Detecting Method in Maritime Environment using Efficient GAN Hiromu Habuka, Kohta Ohshima (TUMSAT) NS2022-230 |
(To be available after the conference date) [more] | NS2022-230 pp.362-367 |
| ICTSSL, CAS | 2023-01-27 14:10 |
Tokyo | TBD (Primary: On-site, Secondary: Online) |
A study on the introduction of managerial workers in crime detection using crowdsourcing Tomoya Nohara (Doshisha Univ.), Ryuya Itano, Takahiro Koita (Graduate School of Doshisha University) CAS2022-89 ICTSSL2022-53 |
In recent years, the number of surveillance cameras installed has been increasing due to the spread of IoT, but there is... [more] | CAS2022-89 ICTSSL2022-53 pp.131-134 |
| NS, ICM, CQ, NV (Joint) |
2022-11-24 14:15 |
Fukuoka | Humanities and Social Sciences Center, Fukuoka Univ. + Online (Primary: On-site, Secondary: Online) |
Research on Anomaly Detection through Analysis of Observed Traffic Using Self-Attention Yuhang Zhou, Akihiro Nakao (UTokyo) NS2022-108 |
Nowadays, threat activities have become an integral part of our network lives. The sophistication and variety of differe... [more] | NS2022-108 pp.47-52 |
| NS, ICM, CQ, NV (Joint) |
2022-11-24 13:25 |
Fukuoka | Humanities and Social Sciences Center, Fukuoka Univ. + Online (Primary: On-site, Secondary: Online) |
Anomaly Detection on Web Pages Using HDBSCAN and Deep SVDD Yusuke Noji, Tomotaka Kimura, Jun Cheng (Doshisha Univ.) CQ2022-51 |
In this paper, we propose an anomalous Web page detection method using Deep SVDD (Support Vector Data Description), whic... [more] | CQ2022-51 pp.23-27 |
| CAS, MSS, IPSJ-AL [detail] | 2022-11-18 14:25 |
Kochi | (Primary: On-site, Secondary: Online) |
How to decide threshold value in anomaly detection using Wireless Ad hoc Federated Learning and Autoencoder Riku Nishihata, Hideya Ochial, Hiroshi Esaki (Univ. Tokyo) CAS2022-55 MSS2022-38 |
Machine learning requires a lot of data, but from the perspective of privacy and security, new learning methods without ... [more] | CAS2022-55 MSS2022-38 pp.83-86 |
| KBSE, SC | 2022-11-05 11:10 |
Nagano | (Primary: On-site, Secondary: Online) |
Smoothing methods for reducing false positives in performance anomaly detection using machine learning Taku Wakui, Mineyoshi Masuda (Hitachi) KBSE2022-41 SC2022-36 |
In the integrated infrastructure management market, ML-based anomaly detection is one of the key features. However, comp... [more] | KBSE2022-41 SC2022-36 pp.60-65 |
| RISING (3rd) |
2022-10-31 10:30 |
Kyoto | Kyoto Terrsa (Day 1), and Online (Day 2, 3) | [Poster Presentation]
Study of Data Collection System for Anomaly Detection by Ultrasonic Components of Mechanical Equipment Operating Sounds Rio Shigyo, Daiki Nobayashi, Kazuya Tsukamoto, Mitsunori Mizumachi, Takeshi Ikenaga (KIT) |
Status checks of mechanical equipment are typically being conducted by workers (manpower) at the actual place. However, ... [more] | |
| NS | 2022-10-05 15:10 |
Hokkaido | Hokkaidou University + Online (Primary: On-site, Secondary: Online) |
An Anomaly Detection System of IoT Traffic for Smart Home Environments Naoto Watanabe, Taku Yamazaki, Takumi Miyoshi (Shibaura Inst. Tech.), Ryo Yamamoto (UEC) NS2022-83 |
With the proliferation of Internet of things (IoT) devices, cyberattacks targeting these devices have also been increasi... [more] | NS2022-83 pp.8-11 |
| IA, CQ, MIKA (Joint) |
2022-09-16 15:45 |
Hokkaido | Hokkaido Citizens Actives Center (Primary: On-site, Secondary: Online) |
Study of Data Collection System for Ultrasonic Waves Based Anomaly Detection of Mechanical Equipment Rio Shigyo, Daiki Nobayashi, Kazuya Tsukamoto, Mitsunori Mizumachi, Takeshi Ikenaga (KIT) IA2022-32 |
Status checks of mechanical equipment are typically being conducted by workers (manpower). However, since the check timi... [more] | IA2022-32 pp.97-102 |
| ITE-ME, EMM, IE, LOIS, IEE-CMN, IPSJ-AVM [detail] | 2022-09-13 13:40 |
Online | Keio Univ. Yagami Campus (Hybrid) (Primary: Online, Secondary: On-site) |
Video Anomaly Detection Method using Deep Learning Models and Crowd Workers Ryuya Itano, Tomoya Nohara, Takahiro Koita (Doshisha Univ.) LOIS2022-10 IE2022-32 EMM2022-38 |
In recent years, the number of surveillance cameras installed has been increasing due to the spread of IoT. However, thi... [more] | LOIS2022-10 IE2022-32 EMM2022-38 pp.1-6 |
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