Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
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) |
(To be available after the conference date) [more] |
|
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) |
(To be available after the conference date) [more] |
|
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 |
Anomaly sound detection of industrial equipment using acoustical features related to timbral attribute 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 |
LOIS, ICM |
2024-01-26 10:10 |
Nagasaki |
Nagasaki Prefectural Art Museum (Primary: On-site, Secondary: Online) |
Service Failure Detection Focusing on Simultaneous Increase in Various Types of Connection Retries in User Traffic Naoki Hayashi, Fumio Katayama, Naoki Tateishi, Osamu Okino, Mitsuho Tahara (NTT) ICM2023-34 LOIS2023-38 |
Many communication services are provided in carrier networks, and these communication services are realized by various e... [more] |
ICM2023-34 LOIS2023-38 pp.33-38 |
IBISML |
2023-12-20 14:55 |
Tokyo |
National Institute of Informatics (Primary: On-site, Secondary: Online) |
Anomaly Detection by One-class Convolution Extreme Learning Machine Using Multiple Kernel Yuta Okami, Takuya Kitamura (NIT, Toyama College) IBISML2023-31 |
In this paper, we propose a one-class convolutional extreme learning machine using multiple kernel. In this method, for ... [more] |
IBISML2023-31 pp.7-12 |
IBISML |
2023-12-20 16:25 |
Tokyo |
National Institute of Informatics (Primary: On-site, Secondary: Online) |
Anomaly detection by deep support data descriptions with pseudo-anomaly data Shuta Tsuchio, Takuya Kitamura (NIT, Toyama college) IBISML2023-34 |
This paper presents deep support vector data description (DSVDD) with pseudo-anomaly data that generated by generative m... [more] |
IBISML2023-34 pp.25-30 |
NS, RCS (Joint) |
2023-12-14 16:00 |
Fukuoka |
Kyushu Institute of Technology Tobata campus, and Online (Primary: On-site, Secondary: Online) |
Evaluation of HttpRequest anomaly detection model using fastText and convolutional autoencoder Haruta Yamada, Ryoichi Kawahara (Toyo Univ.) NS2023-133 |
With the advent of the Internet and its close connection to people's lives, web applications are becoming increasingly i... [more] |
NS2023-133 pp.42-47 |
EMCJ |
2023-11-24 13:00 |
Tokyo |
Kikai-Shinko-Kaikan (Primary: On-site, Secondary: Online) |
Detection Sensitivity Improvement by Removing Reflected Pulse Influence from a Bus Type Network Branch in Sequence Time Domain Reflectometry Takashi Kakiuchi, Kengo iokibe, Yoshitaka Toyota (Okayama Univ) EMCJ2023-73 |
Using the fact that cross-correlation between transmitted and reflected pulses in Sequence Time Domain Reflectometry can... [more] |
EMCJ2023-73 pp.7-12 |
IA |
2023-11-22 16:25 |
Aomori |
Aomori Prefecture Tourist Center ASPM (Aomori) (Primary: On-site, Secondary: Online) |
Improving the accuracy of flow prediction and anomaly detection in GAMPAL, a general-purpose anomaly detection mechanism for Internet traffic Taku Wakui (Keio Univ./Hitachi), Fumio Teraoka (Keio Univ.), Takao Kondo (Hokkaido Univ./Keio Univ.) IA2023-41 |
The authors propose a general-purpose anomaly detection mechanism using Prefix Aggregate without Labeled data (GAMPAL) f... [more] |
IA2023-41 pp.33-40 |