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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| EMT, IEE-EMT | 2018-11-15 11:40 |
Tottori | Kaike Grand Hotel Tensui(Yonago, Tottori) | 3D ground penetrating radar based on adaptive processing of time-domain phase information by using complex-valued self-organizing map Soshi Shimomura, Akira Hirose (Univ. Tokyo)  EMT2018-46 |
We propose an adaptive subsurface 3D visualization system based on a complex-valued self-organizing map (CSOM). Conventi... [more] | EMT2018-46 pp.19-24 |
| CQ, ICM, NS, NV (Joint) |
2018-11-16 09:15 |
Ishikawa | Development of System to Analyze Advanced Attacks Using Self-Organizing Map Akifumi Iwasa, Hikohmi Suzuki (Shinshu Univ.), Tetsuya Ui (NEC) NS2018-140 |
In recent years, the importance of the Internet is increasing. However, DoS / DDoS attacks is increasing. It is difficul... [more] | NS2018-140 pp.57-61 |
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| HCS, HIP, HI-SIGCOASTER [detail] | 2018-05-22 09:30 |
Okinawa | Okinawa Industry Support Center | Clustering of Children Based on Behavior Analysis and Consideration of Individuality Analysis Keiichi Horio, Yuji Watanabe, Tetsuo Furukawa (Kyushu Inst. of Tech.), Takashi Omori (Tamagawa Univ.) HCS2018-13 HIP2018-13 |
In this study, features such as speech, line of sight, response, posture, etc. were extracted from moving images taken b... [more] | HCS2018-13 HIP2018-13 pp.101-106 |
| SANE | 2018-05-14 10:35 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Adaptive processing of time domain information by complex-valued self-organizing map in GPR Soshi Shimomura, Akira Hirose (Tokyo Univ.) SANE2018-2 |
In this technical report, we propose an adaptive subsurface visualization system based on a complex–valued self-organizi... [more] | SANE2018-2 pp.7-11 |
| MBE, NC (Joint) |
2018-03-14 10:00 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Hierarchical quaternion neural networks with self-organizing codebook for unsupervised PolSAR land classification Hyunsoo Kim, Akira Hirose (Tokyo Univ.) NC2017-88 |
We propose a self-organizing codebook-based hierarchical polarization feature vector generation to realize an unsupervis... [more] | NC2017-88 pp.121-126 |
| MBE, NC, NLP (Joint) |
2018-01-26 15:00 |
Fukuoka | Kyushu Institute of Technology | NC2017-54 |
The purpose of this research is to extend Tensor SOM for multi-group analysis. That is, for a set of datasets obatined f... [more] | NC2017-54 pp.23-28 |
| MBE, NC, NLP (Joint) |
2018-01-26 15:50 |
Fukuoka | Kyushu Institute of Technology | Restricted Representation for Attentional Items of Feature Map Developed by a Self-Organizing Map Hiroshi Wakuya, Yuukou Tanaka, Hideaki Itoh (Saga Univ.) NC2017-56 |
A self-organizing map (SOM) can be seen as a signal converter preserving its topology between the input and output space... [more] | NC2017-56 pp.35-40 |
| EMT, IEE-EMT | 2017-11-09 10:50 |
Yamagata | Tendo Hotel (Tendo, Yamagata) | Flexible Unsupervised PolSAR Land Classification System Based on Quaternion Neural Networks Hyunsoo Kim, Akira Hirose (Tokyo Univ.) EMT2017-48 |
We propose a flexible unsupervised PolSAR land classification system based on quaternion neural networks. The existing ... [more] | EMT2017-48 pp.37-42 |
| MBE, NC (Joint) |
2017-10-07 15:40 |
Osaka | Osaka Electro-Communication University | Learning Characteristics of Self-Organizing Map with Adaptive Neighborhood Function Hikari Yoshimi, Hidetaka Ito, Hiroomi Hikawa (Kansai Univ.) NC2017-23 |
This paper proposes a new neighborhood function for the self-organizing map(SOM).As the learning of the SOM progresses,... [more] | NC2017-23 pp.19-24 |
| SANE | 2017-10-05 14:20 |
Tokyo | Maison franco - japonaise (Tokyo) | Unsupervised Adaptive PolSAR Land Classification System Using Quaternion Neural Networks Hyunsoo Kim, Akira Hirose (Univ. of Tokyo) SANE2017-57 |
We propose an unsupervised adaptive PolSAR land classification system using quaternion neural networks. Most of the exis... [more] | SANE2017-57 pp.73-78 |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] | 2017-06-23 14:25 |
Okinawa | Okinawa Institute of Science and Technology | Improvement of The Success Rate of Communication based on Implicit Feedbacks Yuki Fumoto (Computer Mind), Takashi Sato (NIT, Okinawa College) NC2017-5 |
There are two types problems that make communication difficult to establish; one is that concepts formed in each individ... [more] | NC2017-5 pp.1-8 |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] | 2017-06-23 17:40 |
Okinawa | Okinawa Institute of Science and Technology | Kansei analysis of landscape images by Tensor SOM
-- Simultaneous analysis of evaluators, subjects, and evaluation words -- Kyouhei Itonaga (Kyutech), Tohru Iwasaki (Colorcle), Kaori Yoshida, Tetsuo Furukawa (Kyutech) NC2017-12 |
In the field of Kansei evaluation, it is investigated and analyzed by using evaluation words with various subjects and o... [more] | NC2017-12 pp.45-50 |
| SIS | 2017-03-03 11:40 |
Kanagawa | Kanagawa Inst. Tech. Yokohama Office | Hardware implementation of deep neural networks composed of self-organizing maps Yuichiro Tanaka, Hakaru Tamukoh (KIT) SIS2016-60 |
In this research, we aim to implement deep neural networks (DNNs) composed of self-organizing maps into field programmab... [more] | SIS2016-60 pp.101-106 |
| NLP | 2016-12-12 15:25 |
Aichi | Chukyo Univ. | Visualization and Classification by ElasticSOM Yuto Take, Pitoyo Hartono (Chukyo Univ.) NLP2016-89 |
Due to its simplicity, Self-Organizing Maps(SOM) are often utilized to visualize high dimensional data. While SOM is abl... [more] | NLP2016-89 pp.27-32 |
| EMT, IEE-EMT | 2016-11-18 13:20 |
Wakayama | Shirahama Coganoi Resort & Spa | Mitigation of stripe noise problem using a calibration process dependent on antenna RF paths in landmine visualization systems with one-dimensional array antennas Erika Koyama, Akira Hirose (Tokyo Univ.) EMT2016-59 |
We previously presented a landmine visualization system with a one-dimensional array antenna using complex-valued self-o... [more] | EMT2016-59 pp.133-138 |
| RECONF | 2016-09-05 16:00 |
Toyama | Univ. of Toyama | Tomohiro Tanaka, Kazuya Tanigawa, Tetsuo Hironaka (Hiroshima City Univ), Takashi Ishiguro (Taiyo Yuden) RECONF2016-30 |
(To be available after the conference date) [more] | RECONF2016-30 pp.29-34 |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] | 2016-07-06 15:20 |
Okinawa | Okinawa Institute of Science and Technology | Feedforward supervised learning for deep neural networks with local competitiveness information Takashi Shinozaki (NICT) NC2016-15 |
This study proposes a novel supervised learning method for deep neural networks that uses feedforward supervisory signal... [more] | NC2016-15 pp.229-234 |
| SIS | 2016-03-10 14:50 |
Tokyo | Tokyo City Univ. | Evaluation of an information criterion-based growing topology representing network Kazuhiro Tokunaga (NFU) SIS2015-56 |
(To be available after the conference date) [more] | SIS2015-56 pp.49-54 |
| IE, IMQ, MVE, CQ (Joint) [detail] |
2016-03-07 17:55 |
Okinawa | Generation of grid points for 3D-LUT in device calibration based on color discrimination thresholds Masashi Yamamoto, Jinhui Chao (Chuo Univ.) IMQ2015-50 IE2015-149 MVE2015-77 |
In this paper, we propose a method to generate the grid points of 3D Look-Up Table in a color space for device calibrati... [more] | IMQ2015-50 IE2015-149 MVE2015-77 pp.123-128 |
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| NC, NLP (Joint) |
2016-01-28 14:35 |
Fukuoka | Kyushu Institute of Technology | Effect of grouping in vector recognition system Based on SOM Masayoshi Ohta, Ito Daigo, Hiroomi Hikawa (Kansai Univ.) NC2015-56 |
Abstract This paper discusses effect of grouping based on self-organising map．The SOM is a one of unsupervised learning... [more] |
NC2015-56 pp.1-6 |
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