Few-shot object detection based on positive-sample improvement

Traditional object detectors based on deep learning rely on plenty of labeled samples, which are expensive to obtain. Few-shot object detection (FSOD) attempts to solve this problem, learning detection objects from a few labeled samples, but the performance is often unsatisfactory due to the scarcit...

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Bibliographic Details
Main Authors: Yan Ouyang, Xin-qing Wang, Rui-zhe Hu, Hong-hui Xu
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2023-10-01
Series:Defence Technology
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2214914722001660