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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
EMT, IEE-EMT 2021-11-05
11:15		 Online Online Quaternion convolutional neural networks for PolSAR land classification
Yuya Matsumoto, Ryo Natsuaki, Akira Hirose (UTokyo) EMT2021-43		 We propose a quaternion convolutional neural network (QCNN) for Polarimetric synthetic aperture radar
(PolSAR) land cla... [more]		 EMT2021-43
pp.76-81
PRMU 2020-10-09
15:40		 Online Online [Short Paper] Regularized pooling
Takato Otsuzuki, Hideaki Hayashi, Zheng Yuchen, Seiichi Uchida (Kyushu Univ) PRMU2020-31		 In convolutional neural networks (CNNs), pooling operations play important roles such as dimensionality reduction and de... [more] PRMU2020-31
pp.84-89
RECONF 2019-05-10
10:00		 Tokyo Tokyo Tech Front An FPGA Implementation of the Semantic Segmentation Model with Multi-path Structure
Youki Sada, Masayuki Shimoda, Shimpei Sato, Hiroki Nakahara (titech) RECONF2019-10		 Since the convolutional neural network has a high-performance recognition accuracy,
it is expected to implement variou... [more]		 RECONF2019-10
pp.49-54
VLD, DC, CPSY, RECONF, CPM, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC
(Joint) [detail]		 2018-12-05
10:20		 Hiroshima Satellite Campus Hiroshima An FPGA implementation of Tri-state YOLOv2 using Intel OpenCL
Youki Sada, Masayuki Shimoda, Shimpei Sato, Hiroki Nakahara (titech) RECONF2018-35		 Since the convolutional neural network has a high-performance recognition accuracy,
it is expected to implement variou... [more]		 RECONF2018-35
pp.7-12
MBE, NC
(Joint)		 2017-03-13
14:35		 Tokyo Kikai-Shinko-Kaikan Bldg. Convolutional neural networks with 3D input for P300 Identification in auditory brain-computer interfaces
Eduardo Carabez, Miho Sugi, Isao Nambu, Yasuhiro Wada (Nagaoka Gidai) NC2016-71		 We propose a 3D input for a convolutional neural network used as
classifier for an auditory BCI that presents sounds to... [more]		 NC2016-71
pp.43-48
IBISML 2011-11-10
15:45		 Nara Nara Womens Univ. A Linear Time Subpath Kernel for Trees
Daisuke Kimura, Hisashi Kashima (Univ. of Tokyo) IBISML2011-85		 Kernel method is one of the promising approaches to learning with
tree-structured data, and various efficient tree ker... [more]		 IBISML2011-85
pp.291-296
PRMU, NLC 2005-02-25
13:45		 Tokyo   [Special Talk] Kernel Methods for Analyzing Structured-data
Hisashi Kashima (IBM Research) 		We introduce kernel-based approaches for analyzing structured data
such as sequences, trees, and graphs.
Especially,
... [more]		 NLC2004-126 PRMU2004-208
pp.61-66
 Results 1 - 7 of 7  /   
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