Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
SIS, ITE-BCT |
2022-10-13 16:00 |
Aomori |
Hachinohe Institute of Technology (Primary: On-site, Secondary: Online) |
[Invited Talk]
Quasiconformal Mapping and its Application
-- Numerical Method and Application to Machine Learning -- Hirokazu Shimauchi (Hachinohe Inst. of Tech.) SIS2022-14 |
Quasiconformal mapping is a natural generalization of conformal mapping and plays an important role in the areas of math... [more] |
SIS2022-14 pp.17-20 |
EA |
2022-05-13 14:35 |
Online |
Online |
A serial anomalous sound detection method using outlier exposure based on two types of binary classification Ibuki Kuroyanagi (Nagoya Univ.), Tomoki Hayashi (Nagoya Univ./HDL/), Kazuya Takeda, Tomoki Toda (Nagoya Univ.) EA2022-8 |
Anomalous sound detection systems use only normal sound data to detect unknown, atypical sounds. Conventional methods us... [more] |
EA2022-8 pp.35-40 |
IBISML |
2022-03-08 10:25 |
Online |
Online |
Robust computation of optimal transport by β-potential regularization Shintaro Nakamura (Univ. Tokyo), Han Bao (Univ.Tokyo/RIKEN), Masashi Sugiyama (RIKEN/Univ. Tokyo) IBISML2021-31 |
Optimal transport (OT) has become a widely used tool to measure the discrepancy between probability distributions
in th... [more] |
IBISML2021-31 pp.8-14 |
CPSY, DC, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC [detail] |
2021-03-26 10:40 |
Online |
Online |
Unsupervised Recycled FPGA Detection Using Direct Density Ratio Estimation Based on Self-referencing Yuya Isaka (KGU), Michihiro Shintani (NAIST), Foisal Ahmed (PU), Michiko Inoue (NAIST) CPSY2020-60 DC2020-90 |
It is well known that the performance of field-programmable gate-array (FPGA) degrades over time due to their usage. Sev... [more] |
CPSY2020-60 DC2020-90 pp.61-66 |
DC |
2021-02-05 10:55 |
Online |
Online |
Hardware Trojan Detection by Learning Power Side Channel Signals Considering Random Process Variation Michiko Inoue, Riaz-Ul-Haque Mian (NAIST) DC2020-70 |
Due to the globalization and complexity of the supply chain, there is a growing concern about the insertion of hardware ... [more] |
DC2020-70 pp.7-11 |
MBE, MICT |
2021-01-28 15:40 |
Online |
Online |
Consideration about Learning Scheme with Outlier Detection in Training Data for Prediction Model of Medication Effect Using Recurrent Neural Networks Yoshitomo Sakuma, Takumi Kobayashi, Chika Sugimoto, Ryuji Kohno (Yokohama National Univ.) MICT2020-27 MBE2020-32 |
Recently, the application of machine learning to the medical and healthcare field has attracted attention. In particular... [more] |
MICT2020-27 MBE2020-32 pp.28-33 |
CPSY, RECONF, VLD, IPSJ-ARC, IPSJ-SLDM [detail] |
2021-01-25 16:45 |
Online |
Online |
Comparison of ICA Algorithms in the Compressed Sensing EEG Measurement Framework Using OD-ICA Wataru Okumura, Daisuke Kanemoto, Osamu Maida, Tetsuya Hirose (Osaka Univ) VLD2020-52 CPSY2020-35 RECONF2020-71 |
Compressed sensing gives reduction of power consumption for electroencephalogram (EEG) measurement system. However, ocul... [more] |
VLD2020-52 CPSY2020-35 RECONF2020-71 pp.75-79 |
VLD, DC, RECONF, ICD, IPSJ-SLDM (Joint) [detail] |
2020-11-17 14:25 |
Online |
Online |
Energy-Efficient ECG Signals Outlier Detection Hardware Using a Sparse Robust Deep Autoencoder Naoto Soga, Shimpei Sato, HIroki Nakahara (Tokyo Tech) VLD2020-17 ICD2020-37 DC2020-37 RECONF2020-36 |
Advancements in portable electrocardiographs have allowed electrocardiogram (ECG) signals to be recorded in everyday lif... [more] |
VLD2020-17 ICD2020-37 DC2020-37 RECONF2020-36 pp.36-41 |
VLD, DC, CPSY, RECONF, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC (Joint) [detail] |
2019-11-13 10:55 |
Ehime |
Ehime Prefecture Gender Equality Center |
VLD2019-31 DC2019-55 |
In testing of large scale integration (LSI) circuit, test escape detection using machine learning algorithms has been at... [more] |
VLD2019-31 DC2019-55 pp.13-18 |
HWS, VLD |
2019-02-28 13:55 |
Okinawa |
Okinawa Ken Seinen Kaikan |
Model Compression for ECG Signals Outlier Detection Hardware trained by Sparse Robust Deep Autoencoder Naoto Soga, Shimpei Sato, Hiroki Nakahara (Titech) VLD2018-114 HWS2018-77 |
In recent years, portable electrocardiographs and wearable devices have begun to spread so that electrocar- diogram (ECG... [more] |
VLD2018-114 HWS2018-77 pp.127-132 |
VLD, DC, CPSY, RECONF, CPM, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC (Joint) [detail] |
2018-12-06 11:20 |
Hiroshima |
Satellite Campus Hiroshima |
Hardware implementation of ECG signals outlier detector trained by Sparse Robust Deep Autoencoder Naoto Soga, Shimpei Sato, Hiroki Nakahara (Titech) RECONF2018-42 |
Current ECG outlier detection is rule-based, there are many false positives, and it is necessary to study a new outlier ... [more] |
RECONF2018-42 pp.45-50 |
SIS, IPSJ-AVM, ITE-3DMT [detail] |
2018-06-07 14:20 |
Hokkaido |
Jozankei View Hotel |
Estimation of heart rate variability parameters using pulse waved measured by smartphone cameras Yuichiro Tanaka, Akihiro Suzuki (Kyutech), Hirohisa Isogai (Kyushu Sangyo University), Masaaki Iwasaki (Bratech), Hakaru Tamukoh (Kyutech) SIS2018-4 |
Heart rate variability (HRV) parameters are used for analysing activations of autonomic nervous. Generally, the HRV para... [more] |
SIS2018-4 pp.35-38 |
PRMU, CNR |
2017-02-19 11:20 |
Hokkaido |
|
[Poster Presentation]
Online algorithm of swallowing detection using close-range depth sensor Tsubasa Takai, Tomoya Sakai, Misako Higashijima (Nagasaki Univ) PRMU2016-183 CNR2016-50 |
We are developing an online algorithm of detecting and counting swallowing motions from a depth image sequence
for cont... [more] |
PRMU2016-183 CNR2016-50 pp.163-164 |
CPSY, RECONF, VLD, IPSJ-SLDM, IPSJ-ARC [detail] |
2017-01-24 16:55 |
Kanagawa |
Hiyoshi Campus, Keio Univ. |
FPGA Implementation of Mahalanobis Distance-Based Outlier Detection for Streaming Data Yuto Arai, Shin'ichi Wakabayashi, Shinobu Nagayama, Masato Inagi (Hiroshima City Univ.) VLD2016-91 CPSY2016-127 RECONF2016-72 |
This paper focuses on a method to detect outliers in streaming data, and proposes a fast FPGA implementation of outlier ... [more] |
VLD2016-91 CPSY2016-127 RECONF2016-72 pp.141-146 |
ICSS, IPSJ-SPT |
2016-03-04 14:30 |
Kyoto |
Academic Center for Computing and Media Studies, Kyoto University |
An Autonomous DDoS Backscatter Detection System from Darknet Traffic Yuki Ukawa, Jun Kitazono, Seiichi Ozawa (Kobe Univ.), Tao Ban, Junji Nakazato (NICT), Jumpei Shimamura (clwit) ICSS2015-67 |
This paper proposes an autonomous DDoS backscatter detection system from UDP darknet traffic. To identify DDoS backscatt... [more] |
ICSS2015-67 pp.123-128 |
VLD, CPSY, RECONF, IPSJ-SLDM, IPSJ-ARC [detail] |
2016-01-19 14:20 |
Kanagawa |
Hiyoshi Campus, Keio University |
GPGPU Implementation of the MSD Method for Outlier Detection and Its Experimental Evaluation Shotaro Asano, Masato Inagi, Shinobu Nagayama, Shin'ichi Wakabayashi (Hiroshima City Univ.) VLD2015-83 CPSY2015-115 RECONF2015-65 |
In recent years,as the information,communication and sensing technologies advance,data streams have been continuously gr... [more] |
VLD2015-83 CPSY2015-115 RECONF2015-65 pp.37-42 |
MI |
2012-07-20 14:10 |
Yamagata |
Yamagata Univ. |
Performance evaluation of non-rigid robust ICP with statistical shape model Yuki Yaguchi, Takamichi Matsuno, Yoshihide Sawada, Hidekata Hontani (NIT) MI2012-35 |
In this paper, the results of quantitative performance analysis of a robust non-rigid ICP, which was proposed by the aut... [more] |
MI2012-35 pp.73-78 |
MI |
2012-01-19 10:00 |
Okinawa |
|
Robust Non-rigid Cluster-Based Registration with Confidence Self-Evaluation Yoshihide Sawada, Hidekata Hontani (NIT) MI2011-77 |
In this article, we propose a robust non-rigid surface registration method, which registers a surface model to given ima... [more] |
MI2011-77 pp.1-6 |
IBISML |
2011-11-09 15:45 |
Nara |
Nara Womens Univ. |
Relative Density-Ratio Estimation for Robust Distribution Comparison Makoto Yamada (Tokyo Inst. of Tech.), Taiji Suzuki (Univ. of Tokyo), Takafumi Kanamori (Nagoya Univ.), Hirotaka Hachiya, Masashi Sugiyama (Tokyo Inst. of Tech.) IBISML2011-46 |
Divergence estimators based on direct approximation of density-ratios
without going through separate approximation of n... [more] |
IBISML2011-46 pp.25-32 |
IBISML |
2011-11-10 15:45 |
Nara |
Nara Womens Univ. |
A Parametric Programming Approach for Outlier Detection and Robust Learning for Classification and Regression Ichiro Takeuchi (NIT) IBISML2011-81 |
We study outlier detection and robust learning problem for support vector machine (SVM). In the literature there are two... [more] |
IBISML2011-81 pp.263-269 |