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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MICT, MI | 2018-11-06 10:40 |
Hyogo | University of Hyogo | Improvement of Laparoscopic Color Image Diagnosis for Automatic Detection of Coded Defect Region and Application of Effective Classifier Parameter Norifumi Kawabata (Nagoya Univ.), Toshiya Nakaguchi (Chiba Univ.)  MICT2018-42 MI2018-42 |
In addition to judgment by human eyes up to the present, it is advanced for R&D of diagnostic imaging systems by using a... [more] | MICT2018-42 MI2018-42 pp.21-26 |
| IMQ | 2018-10-19 14:40 |
Kyoto | Kyoto Institute of Technology | Classification Method for Texture Types Based on Texture Analysis Results of HEVC Image Quality in the Shitsukan Research Database Norifumi Kawabata (Nagoya Univ.) IMQ2018-13 |
As definition of Shitsukan or Texture, there are many kind of meaning and interpretation. Therefore, there were many stu... [more] | IMQ2018-13 pp.13-18 |
| IMQ | 2017-12-15 13:55 |
Shizuoka | Shizuoka University, Hamamatsu Campus | A Study of Diagnostic Imaging System for Coded Defect Detection of Certain Viewpoints on Multi-view 3D CG Images Norifumi Kawabata (Chiba Univ.) IMQ2017-21 |
At present, in the engineering fields, the medical application for multi-view 3D images and 8K UHDTV images is advanced ... [more] | IMQ2017-21 pp.7-12 |
| HIP | 2017-10-23 16:50 |
Kyoto | Kyoto Terrsa | Reading or Non-reading?
-- Classification of eye movement data using support vector machine -- Nobuyuki Jincho (Waseda Univ.) HIP2017-65 |
(To be available after the conference date) [more] | HIP2017-65 pp.43-46 |
| IMQ, HIP | 2017-07-21 15:00 |
Hokkaido | Satellite Campus, Sapporo City University | Consideration for Application Procedure between H.265/HEVC and Visible Digital Watermarking on the Multi-view 3D CG Image Quality Evaluation Norifumi Kawabata (Chiba Univ.) IMQ2017-8 HIP2017-50 |
In our previous studies, we studied on the multi-view 3D CG image quality evaluation including visible digital watermark... [more] | IMQ2017-8 HIP2017-50 pp.15-20 |
| PRMU, BioX | 2017-03-20 10:00 |
Aichi | Robust Gait Recognition for Carrying-Status by SVM-based Metric Learning using Joint Intensity Histogram Atsuyuki Suzuki, Daigo Muramatsu, Yasushi Makihara, Yasushi Yagi (Osaka Univ.) BioX2016-37 PRMU2016-200 |
This paper describes a method of joint intensity metric learning to improve the robustness of gait recognition under car... [more] | BioX2016-37 PRMU2016-200 pp.23-28 |
|
| CPSY, DC, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC [detail] | 2017-03-10 09:30 |
Okinawa | Kumejima Island | Pass/Fail Prediction in LSI Test Considering Fail Die Characteristics. Takazumi Sato, Michiko Inoue (NAIST) CPSY2016-144 DC2016-90 |
Various kinds of tests are applied to LSIs in several satages to ship only fully reliable products.However, a lot of kin... [more] | CPSY2016-144 DC2016-90 pp.291-296 |
| SIS | 2017-03-02 14:10 |
Kanagawa | Kanagawa Inst. Tech. Yokohama Office | Thermal image diagnosis support system considering tile color for anomaly detection of exterior walls Kazuki Maeda, Katsuya Kondo, Kazu Mishiba, Yuji Oyamada (Tottori Univ.), Makoto Kuramitsu (Sanin Engineering) SIS2016-48 |
In the field of exterior wall inspection, infrared inspection has gotten attention because it is time-saving and safety ... [more] | SIS2016-48 pp.35-40 |
| IE, ITS, ITE-AIT, ITE-HI, ITE-ME, ITE-MMS, ITE-CE [detail] | 2017-02-20 13:15 |
Hokkaido | Hokkaido Univ. | A Note on Selection of Representative Images for Deterioration Diagnosis of Steel Tower Ren Togo, Sho Takahashi, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents an automatic selection method of representative images for deterioration diagnosis of steel towers. ... [more] | |
| PRMU, CNR | 2017-02-18 11:20 |
Hokkaido | Small-sized Kernel Classifier By Support Vector Retraining Based on Minimum Classification Error Criterion Ryoma Tani (Doshisha Univ.), Hideyuki Watanabe (ATR), Shigeru Katagiri, Miho Osaki (Doshisha Univ.) PRMU2016-159 CNR2016-26 |
Different from the Multi-class Support Vector Machine (MSVM) that fixes Support Vectors (SVs) to training samples, the K... [more] | PRMU2016-159 CNR2016-26 pp.41-46 |
|
| NLC, IPSJ-IFAT | 2017-02-09 13:30 |
Osaka | Stock market prediction from Web news using expert articles and machine learning Ko Ichinose, Kazutaka Shimada (KIT) NLC2016-43 |
The market analysis is one of the important tasks for text mining. Many researchers have proposed methods using text inf... [more] | NLC2016-43 pp.19-24 |
|
| MI | 2017-01-18 14:15 |
Okinawa | Tenbusu Naha | A Machine Learning Algorithm for the Automatic and Non-invasive Quality Assessment of Confluent Cells Kazuki Sato (Yamagata Univ.), Hiroto Sasaki, Ryuji Kato (Nagoya Univ.), Tetsuya Yuasa, Siu Kang (Yamagata Univ.) MI2016-98 |
In the research field of regenerative medicine, non-invasive method of cell quality classification has been expected for... [more] | MI2016-98 pp.101-106 |
| MI | 2017-01-18 15:36 |
Okinawa | Tenbusu Naha | Embryonic State Estimation using a Cell Division Timing Masakiyo Nishikawa (NAIST), Yoshihide Sawada, Yumiko O. Kato (Panasonic), Yasuhiro Mukaigawa (NAIST) MI2016-116 |
Confirmation works which check whether the embryo can transplant are necessary in in-vitro fertilization but this works ... [more] | MI2016-116 pp.177-182 |
| IMQ | 2016-12-16 14:20 |
Tokyo | Tokyo University of Technology | Application of Classification Algorithm for the Image Quality Assessment of Multi-view 3D CG Images and 5K Images by Using S-CIELAB Color Space Norifumi Kawabata, Masaru Miyao (Nagoya Univ.) IMQ2016-18 |
Toward the 2020 Tokyo Olympic Games, it is expected that general broadcasting of 4K picture quality will be started. The... [more] | IMQ2016-18 pp.13-18 |
| IBISML | 2016-11-17 14:00 |
Kyoto | Kyoto Univ. | An Exhaustive Search with Support Vector Machine (ES-SVM) for sparse variable selection Daiki Kawabata (UTokyo), Hiroko Ichikawa (TUS), Yasuhiko Igarashi (UTokyo), Kenji Nagata (AIST/JST/UTokyo), Satoshi Eifuku, Ryoi Tamura (Toyama Univ.), Masato Okada (UTokyo) IBISML2016-96 |
Nagata et al.(2015) has proposed Exhaustive Search with Support Vector Machine(ES-SVM) which calculates a cross validati... [more] | IBISML2016-96 pp.361-368 |
| WIT | 2016-10-17 09:00 |
Saga | Karatsu Royal Hotel (Saga pref.) | Gait Identification Using Arm Acceleration Data with SVM Classification Kodai Kitagawa, Yu Taguchi, Nobuyuki Toya (NIT, Kushiro College) WIT2016-39 |
Gait parameters like stride length and foot clearance are important for fall prevention. We have been developing a syste... [more] | WIT2016-39 pp.35-38 |
| IMQ | 2016-05-27 13:40 |
Chiba | Chiba Univ. | Multi-view 3D CG Image Quality Assessment by Using S-CIELAB Color Space Including Visible Digital Watermarking by Regions in case the Background Region is Gray Scale Norifumi Kawabata, Masaru Miyao (Nagoya Univ.) IMQ2016-1 |
Previously, we studied about multi-view 3D CG image quality evaluation including visible digital watermarking by regions... [more] | IMQ2016-1 pp.1-6 |
| NS | 2016-05-19 10:40 |
Kanagawa | Yokohama-shi kyouikukaikan | A Proposal for Supervised Learning Based Automatic Adaptation of Virtualized Resource Selection Policy Takaya Miyazawa, Hiroaki Harai (NICT) NS2016-16 |
It is essential to guarantee quality of services (QoS) by automatically selecting appropriate network and computer resou... [more] | NS2016-16 pp.13-18 |
| PRMU, IE, MI, SIP | 2016-05-19 14:40 |
Aichi | Stent Identification of Circulatory Organ OCT Image Koki Wada, Haiyuan Wu, Kazumasa Suzuki (Wakayama Univ), Takashi Akasaka, Takashi Kubo (Wakayama Medical Univ) SIP2016-7 IE2016-7 PRMU2016-7 MI2016-7 |
In recent years, OCT (Optical Coherence Tomography) has being used to diagnosis the illness in blood vessel.OCT is an im... [more] | SIP2016-7 IE2016-7 PRMU2016-7 MI2016-7 pp.31-36 |
|
| MBE, NC (Joint) |
2016-03-22 09:00 |
Tokyo | Tamagawa University | A Method to Predict New Uses of Existing Drugs Using Machine Learning and to Evaluate Their Reliability Kohei Adachi, Yutaka Fukuoka (Kogakuin Univ.) MBE2015-102 |
This study proposed a method to evaluate the reliability of predicting new uses of existing drugs. The predication was p... [more] | MBE2015-102 pp.1-4 |
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