IEICE Technical Committee Submission System
Conference Schedule
Online Proceedings
[Sign in]
Tech. Rep. Archives
    [Japanese] / [English] 
( Committee/Place/Topics  ) --Press->
( Paper Keywords:  /  Column:Title Auth. Affi. Abst. Keyword ) --Press->

All Technical Committee Conferences  (Searched in: All Years)

Search Results: Conference Papers
 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 29  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU, IPSJ-CVIM 2020-03-17
(Cancelled but technical report was issued)
Object area extraction with biased training data set
Ryo Nakamura, Yoshiaki Ueda, Jun Fujiki, Masaru Tanaka (Fukuoka Univ) PRMU2019-88
In order to extract an object region using machine learning, it is necessary to give a teacher label to each pixel. Prov... [more] PRMU2019-88
PRMU 2019-12-20
Oita   Estimation of $q$-value of $q$-normal distribution through CNN
Yukito Miyakawa, Ryosuke Hosaka, Masaru Tanaka (Fukuoka Univ.) PRMU2019-58
It is usually assumed that the given data follow a normal distribution or $t$ distribution for the sake of simplicity.Th... [more] PRMU2019-58
NC, MBE 2019-12-06
Aichi Toyohashi Tech CNN with Aperture Synthesis -- Toward making anotation tasks simpler and easier --
Ryo Nakamura, Masaru Tanaka, Jun Fuji, Yoshiaki Ueda (Fukuoka Univ) MBE2019-52 NC2019-43
(To be available after the conference date) [more] MBE2019-52 NC2019-43
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2018-06-13
Okinawa Okinawa Institute of Science and Technology 3D Super Resolution Microscopy using Convolutional Neural Network
Masaru Tanaka (Waseda Univ.), Hideitsu Hino (ISM), Shigeyuki Namiki, Daisuke Asanuma, Kenzo Hirose (The Univ. of Tokyo), Noboru Murata (Waseda Univ.) IBISML2018-11
Super-resolution microscopy is a microscopy technique with a resolution beyond the diffraction limit of light. Despite t... [more] IBISML2018-11
PRMU, MVE, IPSJ-CVIM [detail] 2018-01-18
Osaka   Convolutional Neural Network based on Entanglement Entropy and Convolutional Neural Network based on Principal Component Analysis
Shu Eggchee, Masaru Tanaka (Fukuoka Univ.) PRMU2017-129 MVE2017-50
In this paper, we study the differences in the CNN performing processing in accordance with the data using the CNN and e... [more] PRMU2017-129 MVE2017-50
IBISML 2017-11-09
Tokyo Univ. of Tokyo Quantum inspired Machine Learning through Entanglement Entropy
Masaru Tanaka (Fukuoka UNiv.) IBISML2017-50
CNN has been successful in image classification, but we want to focus on the relationship with other fields. In particul... [more] IBISML2017-50
IBISML 2017-11-10
Tokyo Univ. of Tokyo Convolutional Neural Network with Entanglement Entropy
Shu Eguchi, Masaru Tanaka (Fukuoka Univ.) IBISML2017-65
In this paper, we propose a CNN with a process to reduce unnecessary information to identify input data using entangleme... [more] IBISML2017-65
PRMU 2017-10-12
Kumamoto   Entanglement Entropic Convolutional Neural Network
Shu Eguchi, Masaru Tanaka (Fukuoka Univ.) PRMU2017-73
The neural network used for machine learning is an extract that extracts information necessary for classification from e... [more] PRMU2017-73
EE, WPT, IEE-SPC [detail] 2017-07-27
Tokyo Kikai-Shinko-Kaikan Bldg. [Invited Lecture] High-Temperature Rectifier -- An Optimum Temperature of Rectifying Diodes --
Shinji Abe, Masaru Tanaka, Yuki Aoyagi, Hiroki Kuniyoshi, Naoki Sakai, Takashi Ohira (TUT) EE2017-11 WPT2017-16
This report presents ideas, design and implementation for
``IEICE WPT COMPETITION 2017 SPRING - Radio Frequency Rectifi... [more]
EE2017-11 WPT2017-16
PRMU, BioX 2017-03-20
Aichi   Heisemberg group and exponential family -- From the point of view of information geometry --
Akira Tokimatsu, Masaru Tanaka (Fukuoka Univ.) BioX2016-34 PRMU2016-197
(To be available after the conference date) [more] BioX2016-34 PRMU2016-197
PRMU, BioX 2017-03-21
Aichi   On Data Extension For Signal Data
Shu Eguchi, Masaru Tanaka, Jun Fujiki (Fukuoka Univ.), Takio Kurita (Hiroshima Univ.) BioX2016-73 PRMU2016-236
Efficient learning using limited data in machine learning is also important now even in the era of big data. In the case... [more] BioX2016-73 PRMU2016-236
IBISML 2016-11-16
Kyoto Kyoto Univ. [Poster Presentation] Musical Instrument Sound Classification through CNN with Wavelet Analysis
Shu Eguchi, Masaru Tanaka, Jun Fujiki (Fukuoka Univ.), Takio Kurita (Hiroshima Univ.) IBISML2016-51
In music information processing, the instrument sounds analysis using a computer is an important research theme to analy... [more] IBISML2016-51
IBISML 2016-11-16
Kyoto Kyoto Univ. [Poster Presentation] Normal distributions and Heisenberg group -- From the point of view of information geometry --
Akira Tokimatsu, Masaru Tanaka (Fukuoka Univ.) IBISML2016-53
 [more] IBISML2016-53
IBISML 2016-11-17
Kyoto Kyoto Univ. [Poster Presentation] How to make Tsallis entropy become an additive entropy
Masaru Tanaka (Fukuoka Univ.) IBISML2016-99
$tau$-information geometry, that is a new formulation of information geometry, is given by extending a translation opera... [more] IBISML2016-99
Kumamoto Kumamoto National Colle. Technology Capacitive Coupling Wireless Power Transfer Using Mesh Electrodes
Shinji Abe, Yuki Aoyagi, Hiroki Kuniyoshi, Masaru Tanaka, Naoki Sakai, Takashi Ohira (TUT) WPT2015-64
This paper presents capacitive coupling wireless power transfer using mesh electrodes.
Mesh structure has a number of a... [more]
Overseas TamKang University, Tamsui Campus Sakihara-Moebius Harmonometer to Measure Simultaneous Voltage and Current on Nonlinear Devices and Circuits
Masaru Tanaka, Kyohei Yamada, Naoki Sakai, Takashi Ohira (TUT)
IBISML 2015-11-26
Ibaraki Epochal Tsukuba [Poster Presentation] On a family of $q$-normal distributions in the framework of $tau$-information geometry
Masaru Tanaka (Fukuoka Univ.) IBISML2015-62
$tau$-information geometry, that is a new formulation of information geometry, is given by extending a translation opera... [more] IBISML2015-62
PRMU, IBISML, IPSJ-CVIM [detail] 2015-09-14
Ehime   On the statistical properties and parametrization of curved exponential families -- from the view point of $tau$-information geometry --
Masaru Tanaka (Fukuoka Univ.) PRMU2015-69 IBISML2015-29
For curved exponential family, its statistical properties depend on a parameterization. In 1982, Hougaard gives single d... [more] PRMU2015-69 IBISML2015-29
PRMU, IBISML, IPSJ-CVIM [detail] 2015-09-14
Ehime   Curved exponential family fitting in the space of normal distribution
Jun Fujiki, Masaru Tanaka (Fukuoka Univ.), Shotaro Akaho (AIST) PRMU2015-70 IBISML2015-30
We consider the manifold fitting to a given set of points in the space
of probability distributions.
Although only t... [more]
PRMU2015-70 IBISML2015-30
SIP, EA, SP 2015-03-03
Okinawa   [Poster Presentation] Fisher's linear discriminant analysis as a communication of categories
Jun Fujiki, Masaru Tanaka (Fukuoka Univ.), Hitoshi Sakano (NTT Data), Akisato Kimura (NTT) EA2014-102 SIP2014-143 SP2014-165
 [more] EA2014-102 SIP2014-143 SP2014-165
 Results 1 - 20 of 29  /  [Next]  
Choose a download format for default settings. [NEW !!]
Text format pLaTeX format CSV format BibTeX format
Copyright and reproduction : All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)

[Return to Top Page]

[Return to IEICE Web Page]

The Institute of Electronics, Information and Communication Engineers (IEICE), Japan