相关实验视频

追求更好的代表性:平衡可歧视性和可转移性,为少数人进行班级增量学习

Qi Li1, Wei Wang1, Hui Fan2

  • 1National Key Laboratory of Automatic Target Recognition, College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.

Journal of imaging
|November 26, 2025
PubMed
概括

这项研究介绍了BR-FSCIL,这是一种用于少量射击类增量学习 (FSCIL) 的新型框架. 它平衡了代表性的可转移性和可歧视性,在不忘记过去的知识的情况下,提高了基础和新课程的表现.

关键词:
相反的学习学习学习.几次射击的学习学习增量学习是一种增量学习.代表性学习学习学习

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