On fast sample preselection for speeding up convolutional neural network training

Frédéric Rayar, Seiichi Uchida

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

1 被引用数 (Scopus)

抄録

We propose a fast hybrid statistical and graph-based sample preselection method for speeding up CNN training process. To do so, we process each class separately: some candidates are first extracted based on their distances to the class mean. Then, we structure all the candidates in a graph representation and use it to extract the final set of preselected samples. The proposed method is evaluated and discussed based on an image classification task, on three data sets that contain up to several hundred thousands of images.

本文言語英語
ホスト出版物のタイトルStructural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2018, Proceedings
編集者Edwin R. Hancock, Tin Kam Ho, Battista Biggio, Richard C. Wilson, Antonio Robles-Kelly, Xiao Bai
出版社Springer Verlag
ページ65-75
ページ数11
ISBN(印刷版)9783319977843
DOI
出版ステータス出版済み - 2018
イベントJoint IAPR International Workshops on Structural and Syntactic Pattern Recognition, SSPR 2018 and Statistical Techniques in Pattern Recognition, SPR 2018 - Beijing, 中国
継続期間: 8月 17 20188月 19 2018

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11004 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

その他

その他Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition, SSPR 2018 and Statistical Techniques in Pattern Recognition, SPR 2018
国/地域中国
CityBeijing
Period8/17/188/19/18

!!!All Science Journal Classification (ASJC) codes

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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