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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 34  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
RCS 2023-06-14
Hokkaido Hokkaido University, and online
(Primary: On-site, Secondary: Online)
Physical Layer Authentication Based on Mahalanobis Distance Over Spacially Correlated MIMO Channels
Kenta Miwa (UEC), Kengo Ando, Giuseppe Abreu (CU), Koji Ishibashi (UEC) RCS2023-34
This paper focuses on an authentication of a legitimate transmitter over multiple-input multiple-output (MIMO) channels ... [more] RCS2023-34
DC 2021-12-10
(Primary: On-site, Secondary: Online)
Study on Detection Method of the Level Crossing Rod Breakage using the Machine Learning
Hiroshi Shida (NESCO), Noriyuki Shiraishi (JR Shikoku), Hiroshi Takahashi (Ehime Univ) DC2021-62
The level crossing is the only part, which public road intersects a railroad. The level crossing rod is an important equ... [more] DC2021-62
HIP 2021-10-21
Online Online Performance Indicator for Linking Eye and Body Movements
Shuichi Fukuda (Keio Univ) HIP2021-35
With materials getting soft, it becomes necessary to directly interact with objects. Until now, we could understand
h... [more]
DC 2020-12-11
(Primary: On-site, Secondary: Online)
Study on Approach for the NS type Electric Point Machine Maintenance using Condition Based Maintenance
Hiroshi Shida (JR WEST), Yuki Misaki (JR Shikoku), Hiroshi Takahashi (Ehime Univ) DC2020-64
We study on approach for the condition based maintenance (CBM) about NS type electric point machine used widely in Japan... [more] DC2020-64
DC 2019-12-20
Wakayama   Study on Condition-Based Maintenance of Railway Signal Equipment using the Machine Learning
Hiroshi Shida (JR West), Akihiro Tamura, Takashi Ninomiya, Hiroshi Takahashi (Ehime Univ) DC2019-83
Dependable systems are required high safety and reliability. Recently, condition-based maintenance(CBM) is expected to m... [more] DC2019-83
IBISML 2017-11-10
Tokyo Univ. of Tokyo Safe Screening for Large Margin Metric Learning
Tomoki Yoshida (NITech), Ichiro Takeuchi (NITech/NIMS/RIKEN), Masayuki Karasuyama (NITech/NIMS/JST) IBISML2017-64
Large margin metric learning learns the optimal Mahalanobis distance for classification problem based on the margin maxi... [more] IBISML2017-64
CPSY, RECONF, VLD, IPSJ-SLDM, IPSJ-ARC [detail] 2017-01-24
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
BioX, ITE-ME, ITE-IST [detail] 2016-06-20
Ishikawa Ishikawa-Shiko-Kinen-Bunka-Koryukan Personal identification using the characteristics of floor vibration during walking
Ryosuke Sugimoto, Yuma Mano, Juhyon Kim, Kazuki Nakajima (Univ. of Toyama) BioX2016-1
(To be available after the conference date) [more] BioX2016-1
VLD, CPSY, RECONF, IPSJ-SLDM, IPSJ-ARC [detail] 2016-01-19
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
IBISML 2015-11-26
Ibaraki Epochal Tsukuba [Poster Presentation] Approximate Distribution Followed by A Principal Component Term Corresponding with the Population Eigenvalue of zero value in the Q Statistic
Yasuyuki Kobayashi (Teikyo Univ.) IBISML2015-52
The Mahalanobis distance requires all the population eigenvalues of the population covariance matrix larger than zero. H... [more] IBISML2015-52
IBISML 2015-03-05
Kyoto Kyoto University Effects of Numerical Errors against Sample Mahalanobis Distances
Yasuyuki Kobayashi (Teikyo Univ.) IBISML2014-90
I have studied the detail conditions that the numerical errors of sample Mahalanobis distances (T^2=y^' S^(-1) y) of the... [more] IBISML2014-90
IBISML 2014-11-17
Aichi Nagoya Univ. [Poster Presentation] Approximate Models of Probability Distributions for Principal Components of Sample Mahalanobis Distances -- About Each Element and Partial Sum of Sample Mahalanobis Distances --
Yasuyuki Kobayashi (Teikyo Univ.) IBISML2014-37
Probability distributions of the principal components and their partial sum, into which a sample Mahalanobis distance is... [more] IBISML2014-37
IT 2014-07-17
Hyogo Kobe University Distance Metric Learning with Low Computational Complexity based on Ensemble of Low-dimensional Matrixes
Hiroshi Saito, Fumihiro Yamazaki, Kenta Mikawa, Masayuki Goto (Waseda Univ.) IT2014-12
The distance metric learning is the approach which enables to acquire a good metric for automatic data classification. I... [more] IT2014-12
IBISML 2014-03-06
Nara Nara Women's University Study about Over-Learning Phenomenon of Sample Mahalanobis Distances
Yasuyuki Kobayashi (Teikyo Univ.) IBISML2013-70
When the learning sample size n is near the dimensionality p, the discrepant phenomenon between the distribution of the ... [more] IBISML2013-70
PRMU, IPSJ-CVIM, MVE [detail] 2014-01-24
Osaka   *
Wataru Takei, Katsuya Hosobori, Tsuyoshi Kato (Gunma Univ.), Shinichiro Omachi (Tohoku Univ.) PRMU2013-113 MVE2013-54
In computer vision, image crassification has been one of the central
tasks and studied by many researchers.
To deal w... [more]
PRMU2013-113 MVE2013-54
PRMU, IBISML, IPSJ-CVIM [detail] 2013-09-02
Tottori   A proposal of simple correcting scheme for sample Mahalanobis distances using Delta method
Yasuyuki Kobayashi (Teikyo Univ.) PRMU2013-37 IBISML2013-17
In statistical machine learning technology, it is difficult to ignore errors between sample Mahalanobis distances estima... [more] PRMU2013-37 IBISML2013-17
(Joint) [detail]
Kyoto   A Study on Recognition Algorithm of Low Quality Handprinted Characters Using Feature Selection Method Based on the Criterion of Skewness Maximization
Masato Suzuki, Daisuke Kitakoshi (TNCT), Akiyo Matsumoto (Tohoku Gakuin Univ.) PRMU2012-110 MVE2012-75
Mahalanobis distance is a quadratic descriminant function which can reognize handprinted characters
in high accuracy by... [more]
PRMU2012-110 MVE2012-75
PRMU 2012-10-04
Chiba   Construction of the guide system on Android tablets
Yasuaki Miyauti, Yuji Nakagawa (Ehime Univ.) PRMU2012-59
The guide system which shows a visitor the information on a showpiece is offered in a part of museum or art museum. We d... [more] PRMU2012-59
MBE 2011-10-13
Osaka Osaka Electro-Communication University A consideration of diagnosis support to pancreas cancer using data mining from blood exam
Tatsunori Tanaka, Tetsuo Sato, Kotaro Minato (NAIST), Yasushi Matsumura (Osaka U Hospital) MBE2011-52
The purpose of this study is to extract factors correlated with pancreatic cancer and to develop a method of discriminan... [more] MBE2011-52
CPSY, DC, IPSJ-SLDM, IPSJ-EMB [detail] 2011-03-18
Okinawa   Examination of network fault detection method by use of AFM
Isao Shimokawa, Toshiaki Tarui, Hiroki Miyamoto, Tomohiro Baba (hitachi) CPSY2010-71 DC2010-70
We proposed network fault detection method for quickly specifying the router and the server that became a bottleneck in ... [more] CPSY2010-71 DC2010-70
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