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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 16 of 16  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
LOIS, IPSJ-DC 2022-07-07
15:45
Online Online Analysis of interactions between lecturer and students in lectures (Seventh report)
Eiji Watanabe (Konan Univ.), Takashi Ozeki (Fukuyama Univ.), Takeshi Kohama (Kindai Univ.) LOIS2022-9
In lectures using blackboard, we can observe the behaviors (listening to the explanation and taking notes) of students c... [more] LOIS2022-9
pp.30-34
ET 2018-07-14
10:25
Hokkaido National Institute of Technology, Hakodate College Analysis of behaviors by students and page transition (Third report)
Eiji Watanabe (Konan Univ.), Takashi Ozeki (Fukuyama Univ.), Takeshi Kohama (Kindai Univ.) ET2018-19
In this report, we consider a learning environment, which students solve given problems while reading contents consistin... [more] ET2018-19
pp.1-6
ET 2018-03-03
10:50
Kochi Kochi University of Technology (Eikokuji Campus) Analysis of behaviors by students and page transition (Second report)
Eiji Watanabe (Konan Univ.), Takashi Ozeki (Fukuyama Univ.), Takeshi Kohama (Kindai Univ.) ET2017-120
In this report, we consider a learning environment, which students
solve given problems while reading contents consisti... [more]
ET2017-120
pp.183-188
SANE 2016-10-20
14:20
Osaka OIT UMEKITA Knowledge Center [Special Talk] Intelligent Electronic Nose with Metal-Oxide Gas Sensors and its Applicability to Smell Communication
Sigeru Omatu (OIT) SANE2016-40
In this paper, we will show the e-nose system using neural networks and its
application to fire detection system. Fina... [more]
SANE2016-40
pp.3-11
NLP 2013-07-09
10:00
Okinawa Miyako Island Marine Terminal Dynamic Sample Size Selection based quasi-Newton Training for Multilayer Neural Networks
Hiroshi Ninomiya (SIT) NLP2013-38
This paper describes a novel robust training algorithm based on quasi-Newton iteration with the dynamic sample size sele... [more] NLP2013-38
pp.63-68
ET 2013-03-29
13:00
Ehime   A study on the relationship between page transition and understanding for contents
Eiji Watanabe (Konan Univ.), Takashi Ozeki (Fukuyama Univ.), Takeshi Kohama (Kinki Univ.) ET2012-89
In this report, we consider a learning environment, which students
solve the problem while reading contents.
Here, we... [more]
ET2012-89
pp.43-48
NC 2012-07-30
11:35
Shiga Ritsumeikan Univ. College of Information Science and Engineering Noise reduction for images by ensemble learning
Eiji Watanabe (Konan Univ.), Takashi Ozeki (Fukuyama Univ.), Takeshi Kohama (Kinki Univ.) NC2012-16
This report discusses a restoration method for JPEG images based on
ensemble learning algorithm for multiple multi-laye... [more]
NC2012-16
pp.13-18
NC, NLP 2011-01-24
09:30
Hokkaido Hokakido Univ. Parameterized online quasi-Newton Training Algorithm for Feedforward Neural Networks
Hiroshi Ninomiya (SIT) NLP2010-125 NC2010-89
This paper describes a new gradient based technique for training of feedforward neural networks. Recently, improved onli... [more] NLP2010-125 NC2010-89
pp.1-6
NC, MBE
(Joint)
2010-03-10
09:00
Tokyo Tamagawa University Personal Authentication System Using of Minutia Method and Layered Neural Network for Fingerprints Images
Akihiro Tanaka, Shunsuke Onishi, Kentaro Kinoshita, Satoru Kishida (tottori Univ./TEDREC) NC2009-128
We constructed the personal authentication system with learning algorithm of back-propagation using a layered neural net... [more] NC2009-128
pp.237-242
NC, NLP 2009-07-13
14:30
Nara NAIST Estrus Detection of Cattle by Activity using Neural Network
Ryosuke Kawakami, Toru Watanabe (Matsue College of Technology), Makoto Dohi (Shimane Univ.), Motoi Nakashima (Innovit) NLP2009-21 NC2009-14
Cattle breeders in Japan are facing problem of declining productivity by missing estrous sign of maternal cows with resu... [more] NLP2009-21 NC2009-14
pp.37-42
ITE-ME, ITE-AIT, ITE-BCT, IE 2008-11-28
14:10
Nagasaki Nagasaki Univ. Region segmentation for color images based on competitive learning between multi-layered neural networks
Eiji Watanabe (Konan Univ.), Katsumi Mori (Fukuyama Univ.) IE2008-97
Image segmentation plays an important role in image understanding.
It is necessary for such a method to extract each r... [more]
IE2008-97
pp.55-60
NC, MBE
(Joint)
2008-03-14
14:30
Tokyo Tamagawa Univ Construction of Hybrid Authentication System for Voiceprint and Fingerprint
Hikari Kobayashi, Akihiro Tanaka, Satoru Kishida (Tottori Univ.), Toru Watanabe (Matsue National College of Technology), Hiromu Hasegawa (Tottori Univ.) NC2007-183
(To be available after the conference date) [more] NC2007-183
pp.421-426
NC, MBE
(Joint)
2008-03-14
14:50
Tokyo Tamagawa Univ Construction of Voiceprint Personal Authentication System with Hierarchical Neural Network
Akihiro Tanaka, Hikari Kobayashi, Satoru Kishida, Hiromu Hasegawa (Tottori Univ.), Toru Watanabe (Matsue National College of Technology) NC2007-184
We constructed an individual authentication system with three-layered neural networks, where voice was used as a biometr... [more] NC2007-184
pp.427-431
NC 2006-03-17
11:00
Tokyo Tamagawa University Construction of Fingerprint Recognition System on fast fourier transform preprocessing by Layered Neural Network
Akihiro Tanaka, Koichi Nishimura, Satoru Kishida (Tottori Univ.), Toru Watanabe (Matsue NCT), Hiroshi Hasegawa (SECOM SANIN)
We constructed an individual identification system with three-layered neural networks on back-propagation learning algor... [more] NC2005-166
pp.91-96
NC 2006-01-24
11:45
Hokkaido Hokkaido Univ. Personal authentication based on keystrokes by using multi-layered neural networks
Eiji Watanabe (Konan Univ.)
This report discusses a personal authentication method based on the keystroke dynamics, which is extracted from password... [more] NC2005-103
pp.31-35
NLP, CAS 2004-09-14
10:50
Kyoto Kyoto Univ. A study of the learning algorithm based on homotopy method for feedforward neural networks
Chikahiro Tomita (Shizuoka Univ.), Masahiro Yoshida (SHARP), Hiroshi Ninomiya (SIT), Hideki Asai (Shizuoka Univ.)
Many kinds of gradient methods have been applied for learning of the feedforward neural networks in order to improve the... [more] CAS2004-32 NLP2004-44
pp.25-29
 Results 1 - 16 of 16  /   
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