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Class incremental learning via feature space calibration

Jeonghoon Kim Jinming Cao Jihie Kim Roger Zimmermann Seongsik Park

计算可视媒体(英文)2025,Vol.11Issue(5):1025-1039,15.
计算可视媒体(英文)2025,Vol.11Issue(5):1025-1039,15.DOI:10.26599/CVM.2025.9450426

Class incremental learning via feature space calibration

Class incremental learning via feature space calibration

Jeonghoon Kim 1Jinming Cao 2Jihie Kim 1Roger Zimmermann 2Seongsik Park3

作者信息

  • 1. Dongguk University,Seoul,Republic of Korea
  • 2. School of Computing,National University of Singapore,Singapore
  • 3. Korean National Open University,Seoul,Republic of Korea
  • 折叠

摘要

关键词

incremental learning/loss function/deep learning/image classification

Key words

incremental learning/loss function/deep learning/image classification

引用本文复制引用

Jeonghoon Kim,Jinming Cao,Jihie Kim,Roger Zimmermann,Seongsik Park..Class incremental learning via feature space calibration[J].计算可视媒体(英文),2025,11(5):1025-1039,15.

基金项目

This research was supported by the Ministry of Science and ICT,Republic of Korea,under the Information Technology Research Center Support Program(IITP-2024-2020-0-01789),and the Artifi-cial Intelligence Convergence Innovation Human Resources Development(IITP-2024-RS-2023-00254592)supervised by the Institute for Information &Communications Technology Planning & Evaluation(IITP).This research was also supported by the National Research Foundation,Singapore,and Ministry of National Development,Singapore,under its Cities of Tomorrow R&D Programme(CoT NRF-CoT-V4-2020-9).Any opinions,findings,conclusions,and recommendations expressed in this material are those of the authors and do not reflect the views of the Singaporean National Research Foundation,Ministry of National Development,National Parks Board,or Housing Development Board.We would also like to acknowledge the National Parks Board for comments and assistance with providing locality information and images of flora and fauna used in this project. (IITP-2024-2020-0-01789)

计算可视媒体(英文)

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