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Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU, IBISML, IPSJ-CVIM [detail] 2017-09-15
16:20		 Tokyo   Ridge Regression for Improving the Accuracy of k-Nearest Neighbor Classification
Yutaro Shigeto (CIT), Masashi Shimbo, Yuji Matsumoto (NAIST) PRMU2017-53 IBISML2017-25		 This paper proposes an inexpensive way to learn an effective dissimilarity function to be used for $k$-nearest neighbor ... [more] PRMU2017-53 IBISML2017-25
pp.113-119
PRMU, IE, MI 2010-05-14
14:45		 Aichi Chubu Univ. An Analysis of the Impact of a Training Dataset Expansion for Generic Object Recognition
Takumi Toyama, Koichi Kise (Osaka Prefecture Univ.) IE2010-40 PRMU2010-28 MI2010-28		 In the field of pattern recognition, it is well known that the contents of a training dataset affects the recognition pe... [more] IE2010-40 PRMU2010-28 MI2010-28
pp.145-150
IE, ITE-BCT, ITE-AIT, ITE-ME 2004-11-26
09:30		 Nagasaki   Pattern Classification Using Distance Weighted Average Pattern of k Nearest Neighbors
Seiji Hotta, Senya Kiyasu, Sueharu Miyahara (Nagasaki Univ.) 		The recognition rate of the typical nonparametric method ``$k$-Nearest Neighbor rule ($k$NN)" is degraded when the dimen... [more] IE2004-86
pp.1-4
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