Optimal Rejection Function Meets Character Recognition Tasks

Xiaotong Ji, Yuchen Zheng, Daiki Suehiro, Seiichi Uchida

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

In this paper, we propose an optimal rejection method for rejecting ambiguous samples by a rejection function. This rejection function is trained together with a classification function under the framework of Learning-with-Rejection (LwR). The highlights of LwR are: (1) the rejection strategy is not heuristic but has a strong background from a machine learning theory, and (2) the rejection function can be trained on an arbitrary feature space which is different from the feature space for classification. The latter suggests we can choose a feature space which is more suitable for rejection. Although the past research on LwR focused only its theoretical aspect, we propose to utilize LwR for practical pattern classification tasks. Moreover, we propose to use features from different CNN layers for classification and rejection. Our extensive experiments of notMNIST classification and character/non-character classification demonstrate that the proposed method achieves better performance than traditional rejection strategies.

本文言語英語
ホスト出版物のタイトルPattern Recognition - 5th Asian Conference, ACPR 2019, Revised Selected Papers
編集者Shivakumara Palaiahnakote, Gabriella Sanniti di Baja, Liang Wang, Wei Qi Yan
出版社Springer
ページ169-183
ページ数15
ISBN(印刷版)9783030412982
DOI
出版ステータス出版済み - 1 1 2020
イベント5th Asian Conference on Pattern Recognition, ACPR 2019 - Auckland, ニュージ―ランド
継続期間: 11 26 201911 29 2019

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)
12047 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

会議

会議5th Asian Conference on Pattern Recognition, ACPR 2019
国/地域ニュージ―ランド
CityAuckland
Period11/26/1911/29/19

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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