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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NLP | 2024-09-05 13:50 |
Gifu | Takayama City Library | ECG anomaly detection based on time series forecasting using chaotic neural network reservoir Tatsuya Saito, Misa Fujita, Akito Ishihara (Chukyo Univ.)  NLP2024-45 |
(To be available after the conference date) [more] | NLP2024-45 pp.21-25 |
| SIP | 2024-08-27 11:25 |
Fukui | University of Fukui (Bunkyo Campus) (Primary: On-site, Secondary: Online) |
[Invited Talk]
On anomaly detection of software systems by logs Riku Akema (AMIYA Corp.) SIP2024-56 |
Logs output by software systems in, e.g., servers and network devices, are important for monitoring the system's operati... [more] | SIP2024-56 p.57 |
| SIP | 2024-08-27 13:15 |
Fukui | University of Fukui (Bunkyo Campus) (Primary: On-site, Secondary: Online) |
Optimization of Learning Data for Improving Accuracy in Bearing Anomaly Detection Using GMM Shota Okuda, Haruhiro Takemura (TUS), Ghassan Al-Falouji (Univ. of Kiel), Gerald Schickhuber, Armin Sehr, Roland Mandl (OTH Regensburg), Takahiro Yoshida (TUS) SIP2024-57 |
A large number of bearings are used in machines such as in factory production lines. Significant losses will be incurred... [more] | SIP2024-57 pp.58-62 |
| RCC, RCS, SeMI, NS, SR, RISING (Joint) |
2024-07-17 10:00 |
Hokkaido | Hokkaido Citizens Activities Promotion Center (Primary: On-site, Secondary: Online) |
[Short Paper]
A Study on Random Walk SGD for Fault-Tolerance Decentralized Federated Learning Yuta Tomimasu, Koya Sato (UEC) SR2024-22 |
Random walk stochastic gradient descent (RWSGD) is an optimization algorithm for communication-efficient decentralized f... [more] | SR2024-22 pp.1-3 |
| RCC, RCS, SeMI, NS, SR, RISING (Joint) |
2024-07-17 16:05 |
Hokkaido | Hokkaido Citizens Activities Promotion Center (Primary: On-site, Secondary: Online) |
A Study of How to Apply Wi-Fi Sensing to Outdoor Anomaly Detection
-- for Crop Protection from Wildlife Damage -- Toshinori Suzuki, Yu Morishima (Tohoku-Gakuin Univ.), Shin-ichiro Ogura (Tohoku Univ.), Hiroshi Matsuura (Tohoku-Gakuin Univ.) SeMI2024-20 |
In order to reduce crop damage, the authors are considering methods to detect and threaten wild animals invading farmlan... [more] | SeMI2024-20 pp.34-39 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-20 14:20 |
Okinawa | OIST | Anomaly Detection in the Frequency Domain with Statistical Reliability Akifumi Yamada, Kouichi Taji (Nagoya Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN) NC2024-7 IBISML2024-7 |
There are many applications of artificial intelligence (AI) in the field of anomaly detection in the frequency domain fo... [more] | NC2024-7 IBISML2024-7 pp.43-50 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-20 15:25 |
Okinawa | OIST | Selective Inference for Anomaly Detection using Diffusion Models Teruyuki Katsuoka, Tomohiro Shiraishi (Nagoya Univ.), Daiki Miwa (NITech), Vo Nguyen Le Duy (RIKEN), Ichiro Takeuchi (Nagoya Univ./RIKEN) NC2024-9 IBISML2024-9 |
In recent years, there has been active research on anomaly detection using diffusion models, which are generative models... [more] | NC2024-9 IBISML2024-9 pp.60-66 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-22 11:40 |
Okinawa | OIST | Hierarchical reservoir computing model with circle topology for time series prediction and anomaly detection Wenkai Yu, Satoshi Moriya, Hideaki Yamamoto, Shigeo Sato (Tohoku Univ) NC2024-31 IBISML2024-31 |
Reservoir computing (RC), known for its high resource efficiency and ability to handle dynamic data, is gaining attentio... [more] | NC2024-31 IBISML2024-31 p.188 |
| ICM, IPSJ-IOT, IPSJ-CSEC | 2024-05-31 09:00 |
Tottori | (Primary: On-site, Secondary: Online) |
Failure Point Localization Technique with Anomaly Detection Reiko Kondo, Takeshi Kodama, Takashi Shiraishi (FSAS TECHNOLOGIES) ICM2024-4 |
As systems become more complex due to virtualization, dependencies between virtual and physical components can cause the... [more] | ICM2024-4 pp.15-20 |
| EA | 2024-05-22 15:20 |
Online | Online | An anomalous sound detection for industrial machines using acoustical features related to timbral-based metrics Yasuji Ota, Ryoya Ogura, Masashi Unoki (JAIST) EA2024-6 |
In this paper, we proposed a method for detecting anomaly sound of industrial equipment based on timbre-related features... [more] | EA2024-6 pp.23-28 |
| ICM | 2024-03-22 15:25 |
Okinawa | Okinawa Prefectural Museum and Art Museum (Primary: On-site, Secondary: Online) |
Study of AI Model Training Method Using Network Digital Twin in Scale-out 5GC Environment Daiki Koyama, Minato Sakuraba, Junichi Kawasaki, Takuya Miyasaka (KDDI Research) ICM2023-62 |
This technical report proposes a method for building AI models for network operations by utilizing the network digital t... [more] | ICM2023-62 pp.89-94 |
| WIT, IPSJ-AAC | 2024-03-19 15:10 |
Ibaraki | Tsukuba University of Technology (Primary: On-site, Secondary: Online) |
Anomaly Detection Method of Elderly using Human Body Surface Temperature Tasuku Hanato, Shin Morishima, Akira Urashima (TPU), Hiroshi Minematsu, Takashi Yamamoto (Shikino High-Tech Co., Ltd.), Tomoji Toriyama (TPU) WIT2023-55 |
Detecting Anomalies in bedridden elderly humans is an important issue. However, it is difficult for caregivers to consta... [more] | WIT2023-55 pp.69-74 |
| IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-14 16:20 |
Okinawa | Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
Detection and Tracking of Abnormal Objects in Forests from Dynamic Time-sequential RGBD Images Based on Deep Learning Segment Anything Yuta Suzuki (Waseda Univ.), Junji Yamato (Kougakuin Univ.), Jun Ohya (Waseda Univ.) IMQ2023-59 IE2023-114 MVE2023-88 |
This paper proposes a method for distinguishing changes caused by abnormal objects such as illegal dumping and fallen tr... [more] | IMQ2023-59 IE2023-114 MVE2023-88 pp.252-257 |
| IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-15 15:30 |
Okinawa | Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
High Precision Anomaly Detection using PaDiM based on Pre-training with Normality Constraint of Normal Features Hiroki Kobayashi, Manabu Hashimoto (Chukyo Univ.) IMQ2023-89 IE2023-144 MVE2023-118 |
In recent years, automatic visual inspection is expected with machine learning. Among them, PaDiM is attracting attentio... [more] | IMQ2023-89 IE2023-144 MVE2023-118 pp.408-413 |
| IA, SITE, IPSJ-IOT [detail] | 2024-03-12 15:35 |
Okinawa | Miyakojima City Future Creation Center (Primary: On-site, Secondary: Online) |
Data Analysis and Visualization Method for Equipment Anomaly Detection by Using Acoustic Data Koichiro Kawano, Nobayashi Daiki, Tsukamo Kazuya, Mizumachi Mitsunori, Ikenaga Takeshi (KIT) SITE2023-82 IA2023-88 |
Manual inspections of general equipment present many challenges in terms of manpower, time, and labor costs. In addition... [more] | SITE2023-82 IA2023-88 pp.86-91 |
| MI | 2024-03-03 11:40 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Weak supervised chest lesion detection on FDG-PET/CT Images using Pix2Pix image modality translation Kazuki Otani, Kohei Yoshida, Mitsutaka Nemoto (Kindai Univ.), Hayato Kaida (KU Hosp), Yuichi Kimura, Takashi Nagaoka, Katsuhiro Mikami (Kindai Univ.), Takahiro Yamada, Kohei Hanaoka (KU Hosp), Tsuchitani Tatsuya, Kazuhiro Kitajima (HMU Hosp), Kazunari Ishii (KU Hosp) MI2023-42 |
In this study, we propose a method for detecting thoracic lesions on PET/CT images using 3D Pix2Pix, which learns a tran... [more] | MI2023-42 pp.36-38 |
| MI | 2024-03-04 14:12 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Anomaly Detection for Lung CT Images Using VQ-VAE with SVDD Zhihui Gao, Ryohei Nakayama, Aikiyoshi Hizukuri (Ritsumeikan Univ.), Shoji Kido (Oosaka Univ.) MI2023-80 |
In this study, VQ-VAE with SVDD for anomaly detection in CT images was constructed by introducing a support vector data ... [more] | MI2023-80 pp.158-159 |
| 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 |
| ITS, IE, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2024-02-20 13:15 |
Hokkaido | Hokkaido Univ. | DoG-PaDiM:Anomaly Detection with Defect Size Selectivity based on Bandpass Filtering Naoto Hiramatsu, Naoki Murakami, Hiroki Kobayashi, Shuichi Akizuki, Manabu Hashimoto (Chukyo Univ.) ITS2023-69 IE2023-58 |
In the background of the increasing precision of visual inspections, recently, anomaly detection methods using machine l... [more] | ITS2023-69 IE2023-58 pp.124-129 |
| NS, NWS (Joint) |
2024-01-25 13:00 |
Hiroshima | Higashisenda Campus, HiroshimaUniversity + Online (Primary: On-site, Secondary: Online) |
[Encouragement Talk]
Performance evaluation of network anomaly detection and failure scale estimation method. Naoya Ogawa, Ryoichi Kawahara (Toyo Univ.) NS2023-159 |
In this paper, we evaluate the performance of the method proposed in "Network anomaly detection and failure scale estima... [more] | NS2023-159 pp.1-6 |
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