Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
PRMU, CNR |
2015-02-20 16:00 |
Miyagi |
|
Detection of irregular behavior patterns based on comprehensive movement of people Kizuku Nishimura, Shigeki Aoki, Takao Miyamoto (Osaka Prefecture Univ.) PRMU2014-156 CNR2014-71 |
Automatic video surveillance systems have recently become an active area of research.Typical methods of research can be ... [more] |
PRMU2014-156 CNR2014-71 pp.221-226 |
PRMU, IPSJ-CVIM, MVE [detail] |
2015-01-23 10:15 |
Nara |
|
Relation between Data Grouping and Robustness to Unseen Data in Large Geometric Margin Minimum Classification Error Training Hiroyuki Shiraishi (Doshisha Univ), Hideyuki Watanabe (NICT), Shigeru Katagiri (Doshisha Univ), Xugang Lu, Chiori Hori (NICT), Miho Ohsaki (Doshisha Univ) PRMU2014-101 MVE2014-63 |
To develop a pattern classifier that is robust to unseen pattern samples, classifier parameters have been conventionally... [more] |
PRMU2014-101 MVE2014-63 pp.177-182 |
ICM, LOIS |
2015-01-16 10:10 |
Fukuoka |
Kanmon Straits & Mojiko Retro |
Life sound discrimination algorithm using Neural network Hiroyuki Nishi, Kin Kin, Yoshimasa Kimura, Toshio Kakinoki (Sojo Univ) ICM2014-43 LOIS2014-50 |
In an aging society, the death of elderly people living alone has become a serious social problem. Conventional observat... [more] |
ICM2014-43 LOIS2014-50 pp.61-65 |
PRMU |
2014-12-12 10:00 |
Fukuoka |
|
Improvement of Feature Space Construction for Pattern Representation on Data Compression Yuji Nakajima, Hisashi Koga, Takahisa Toda (UEC) PRMU2014-76 |
Recent years have witnessed an increased interest about compression-based methods, which is basically parameter-free app... [more] |
PRMU2014-76 pp.63-68 |
PRMU |
2014-12-12 13:00 |
Fukuoka |
|
A proposal for data selection in self-training based cross dataset action recognition Takafumi Suzuki, Yu Wang, Jien Kato, Kenji Mase (Nagoya Univ) PRMU2014-80 |
In action recognition, in order to obtain high performance classifiers, it is necessary to feed the training algorithm e... [more] |
PRMU2014-80 pp.85-89 |
VLD, DC, IPSJ-SLDM, CPSY, RECONF, ICD, CPM (Joint) [detail] |
2014-11-26 16:15 |
Oita |
B-ConPlaza |
General-Purpose Pattern Recognition Processor Based on the k Nearest-Neighbor Algorithm with High-Speed, Low-Power Shogo Yamasaki, Toshinobu Akazawa, Fengwei An, Hans Juergen Mattausch (Hiroshima Univ.) VLD2014-75 DC2014-29 |
A learning and pattern recognition processors for the k nearest neighbor (k-NN) recognition algorithm using a nearest Eu... [more] |
VLD2014-75 DC2014-29 pp.21-26 |
IE, EMM, LOIS, IEE-CMN, ITE-ME [detail] |
2014-09-18 11:30 |
Kochi |
|
Life sound identification algorithm using pattern recognition Hiroyuki Nishi, Kin Kin, Yoshimasa Kimura, Toshio Kakinoki (Sojo Univ.) LOIS2014-17 IE2014-30 EMM2014-47 |
In an aging society, the death of elderly people living alone has become a serious social problem.
In this study, we ... [more] |
LOIS2014-17 IE2014-30 EMM2014-47 pp.1-4 |
IE, EMM, LOIS, IEE-CMN, ITE-ME [detail] |
2014-09-18 17:35 |
Kochi |
|
[Invited Talk]
Pedestrian Detection with an In-Vehicle Camera Guoyue Chen, Xingguo Zhang, Kazuki Saruta, Yuki Terata (Akita Prefectural Univ.) LOIS2014-24 IE2014-37 EMM2014-54 |
Every year almost 1 million people are killed in traffic crashes. Over the past twenty years, research has moved toward ... [more] |
LOIS2014-24 IE2014-37 EMM2014-54 p.59 |
NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] |
2014-06-26 15:50 |
Okinawa |
Okinawa Institute of Science and Technology |
Pattern Recognition using feature extractor of K-SVD Hiroki Sugita (UEC), Hiroaki Sasaki (Tokyo Inst. of Tech.), Hayaru Shouno (UEC) NC2014-7 IBISML2014-7 |
Feature extraction and classification are fundamental two steps in pattern recognition systems. Since feature extraction... [more] |
NC2014-7 IBISML2014-7 pp.101-106 |
NC, MBE (Joint) |
2014-03-17 11:00 |
Tokyo |
Tamagawa University |
Correlation between voice signals and alcohol concentrations in blood Masayuki Kawanoi, Naoki Fujiwara, Satoru Kishida (Tottori Univ.) NC2013-117 |
We investigated the correlation between voice signals and alcohol concentrations in blood with neural network systems fo... [more] |
NC2013-117 pp.167-170 |
PRMU |
2014-03-14 15:00 |
Tokyo |
|
Feature Extraction Using Local Gradient Pattern Hiroki Terashima, Takuya Kida (Hokkaido Univ.) PRMU2013-209 |
Local Binary Pattern (LBP) is an image feature that widely used for image classification.This feature consists of a hist... [more] |
PRMU2013-209 pp.247-252 |
ICD, IPSJ-ARC |
2014-03-07 10:15 |
Aichi |
|
Flexible Word-Parallel Euclidean Distance Search Associative Memory for Applications with Varying Dimensionality of Reference Vectors Toshinobu Akazawa, Hans Jurgen Mattausch (Hiroshima Univ.) ICD2013-138 |
The reported fully word-parallel associative memory architecture for nearest Euclidean distance (ED) search, which has f... [more] |
ICD2013-138 pp.33-37 |
ITS, IE, ITE-AIT, ITE-HI, ITE-ME [detail] |
2014-02-18 13:35 |
Hokkaido |
Hokkaido Univ. |
HOG Feature based Polar Coordinates for Pedestrian Detection Yuta Horikawa, Kousuke Matsushima (KurumeNCT) ITS2013-65 IE2013-130 |
Recently, the number of traffic accidents and injured people has been decreasing. However, the traffic-related pedestria... [more] |
ITS2013-65 IE2013-130 pp.357-362 |
PRMU, CNR |
2014-02-13 13:00 |
Fukuoka |
|
[Special Talk]
Robotic Service Perspective with Research Fields of Pattern Recognition and Media Understanding (PRMU) and Cloud Networked Robotics(CNR)
-- - -- Norihiro Hagita (ATR) PRMU2013-128 CNR2013-36 |
Robots have three “robotic” functions: sensation, actuation, and intelligent control. Cloud networked robotics is a new ... [more] |
PRMU2013-128 CNR2013-36 pp.41-46 |
PRMU, CNR |
2014-02-13 15:00 |
Fukuoka |
|
Improved Subspace-based Support Vector Machines by linear combination of the separating hyper-planes Shota Funaki, Takuya Kitamura (TNCT) PRMU2013-135 CNR2013-43 |
In this paper, we propose the improved subspace-based SVMs (SS-SVMs) by linearly-combining the separating hyper-planes (... [more] |
PRMU2013-135 CNR2013-43 pp.77-82 |
ICD |
2014-01-28 15:00 |
Kyoto |
Kyoto Univ. Tokeidai Kinenkan |
[Poster Presentation]
Digital Word-Parallel Associative Memory for Smallest Euclidean Distance Search and Architecture verification in 180nm/65nm CMOS Toshinobu Akazawa, Hans Juergen Mattausch (Hiroshima Univ.) ICD2013-132 |
The reported digital word-parallel associative memory architecture for nearest Euclidean distance (ED) search is based o... [more] |
ICD2013-132 p.77 |
ICD |
2014-01-29 14:00 |
Kyoto |
Kyoto Univ. Tokeidai Kinenkan |
Development of a Learning and Recognition SoC Based on the k Nearest-Neighbor Algorithm with High-Speed, Low-Power and Error-Free Operation Shogo Yamasaki, Toshinobu Akazawa, Fengwei An, Hans Juergen Mattausch (Hiroshima Univ) ICD2013-136 |
In this study, we propose the hardware implementation of the k-nearest neighbor method on an SoC with learning and recog... [more] |
ICD2013-136 pp.85-88 |
PRMU, IPSJ-CVIM, MVE [detail] |
2014-01-23 10:30 |
Osaka |
|
Rhythm and Music Generation from Performance Motion in Gravity Point of Upper Body Hiroki Kawaguchi, Arisa Hayashi, Yosuke Ino, Naoto Yoshida, Tomoko Yonezawa (Kansai Univ.) PRMU2013-97 MVE2013-38 |
In this paper, we introduce an investigation of relationship between the music tune and the movement of human body durin... [more] |
PRMU2013-97 MVE2013-38 pp.49-52 |
SIS |
2013-12-12 13:50 |
Tottori |
Torigin Bunka Kaikan (Tottori) |
Correlation between voice signals and alcohol concentrations in blood Masayuki Kawanoi, Naoki Fujiwara, Hiroki Yoshimura, Satoru Kishida (Tottori Univ.) SIS2013-37 |
We clarified the correlation between voice signals and alcohol concentrations in blood by using neural network systems f... [more] |
SIS2013-37 pp.59-62 |
EMM, EA |
2013-11-14 15:45 |
Hiroshima |
Prefectural University of Hiroshima, Satellite Campus Hiroshima |
Information Embedment to Character Patterns Using Color Shohei Okugi, Yoshihiro Sugaya, Shinichiro Omachi (Tohoku Univ.) EA2013-73 EMM2013-73 |
With development of cyber physical systems, information hiding technology that goes through the real environment has bee... [more] |
EA2013-73 EMM2013-73 pp.31-36 |