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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 9 of 9  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
EMM, EA, ASJ-H 2023-11-23
13:00
Toyama   [Poster Presentation] A Study of Complexity Reduction for Classification of Musical Instruments Using Element Selection
Ryu Kato, Natsuki Ueno, Nobutaka Ono (Tokyo Metropolitan Univ.), Ryo Matsuda, Kazunobu Kondo (Yamaha Corp.) EA2023-37 EMM2023-68
In this study, we propose complexity reduction in convolutional-neural-network (CNN)-based music instruments classificat... [more] EA2023-37 EMM2023-68
pp.51-56
WIT 2023-06-17
15:20
Okinawa Okinawa Industry Support Center
(Primary: On-site, Secondary: Online)
Improved Visual Intentions Estimation Model Using Depth Information and Object Detection
Sho Higa, Masakiyo Okuhama, Koji Yamada (Ryukyu Univ.), Shihoko Kamisato (NIT,Okinawa College) WIT2023-17
In this study, we propose an improved visual intention estimation model based on object detection to distinguish eye and... [more] WIT2023-17
pp.76-77
PRMU 2018-12-13
10:30
Miyagi   Candidate Reduction Method Using Hierarchical Overlapping Clustering and Convolutional Neural Network for Fast Chinese Character Recognition
Soichi Tashima, Hideaki Goto (Tohoku Univ.) PRMU2018-77
Along with the widespread of the mobile devices equipped with cameras, many applications using the camera function have ... [more] PRMU2018-77
pp.13-18
NC, NLP
(Joint)
2017-01-26
16:25
Fukuoka Kitakyushu Foundation for the Advanement of Ind. Sci. and Tech. Estimation of respiratory state using machine learning
Keisuke Matsuoka, Jiro Okuda (Kyoto Sangyo Univ.) NC2016-53
Recent studies have tried to extract information on respiration from photoplethysmographic (PPG) signals. It is well kno... [more] NC2016-53
pp.31-36
SP, IPSJ-SLP, NLC, IPSJ-NL
(Joint) [detail]
2016-12-20
11:20
Tokyo NTT Musashino R&D Speaker Recognition Based on Features through 1-Dimensional Convolutional Neural Network
Shohei Sonoda, Yufu Kasahara, Masato Inoue (Waseda Univ) SP2016-52
Most of the speaker recognition methods utilize the voice features of the mel-frequency cepstrum coefficients (MFCCs) an... [more] SP2016-52
pp.17-21
PRMU 2009-03-14
10:45
Miyagi Tohoku Institute of Technology *
Aiko Oka, Toshikazu Wada (Wakayama Univ.) PRMU2008-267
This paper presents a regression method, two-dimensional Mahalanobis distance minimization mapping (2D-M3), which is an ... [more] PRMU2008-267
pp.183-190
PRMU 2006-03-17
14:00
Fukuoka Kyushu Univ. Non-Iterative Two-Dimensional Linear Discriminant Analysis for Face Recognition
Kohei Inoue, Kiichi Urahama (Kyushu Univ.)
Linear discriminant analysis (LDA) is a well-known scheme for feature extraction and dimensionality reduction of labeled... [more] PRMU2005-286
pp.179-182
PRMU, NLC 2005-09-22
13:10
Tokyo   An Evaluation of Pseudo 3-Dimentional Vector Feature Extraction Method -- An Improved Correlation Method for Character Recognition --
Marie Nikaido, Koji Kitamura, Yumi Nakashima, Michio Yasuda (Meisei Univ.)
We evaluate a pseudo 3-dimensional and directional features extraction method which previously reported.

This method ... [more]
NLC2005-49 PRMU2005-76
pp.77-82
PRMU 2005-01-21
09:30
Kyoto   A Proposal for Pseudo 3-Dimensional and Directional Feature Extraction Method -- An Improved Correlation Method for Character Recognition --
Marie Nikaido, Koji Kitamura, Yumi Nakashima, Michio Yasuda (Meisei Univ.)
We propose the pseudo 3-dimensional and directional feature extraction
method for the character recognition method us... [more]
PRMU2004-164
pp.7-12
 Results 1 - 9 of 9  /   
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