Complementary Local–Global Optimization for Few-Shot Object Detection in Remote Sensing

Complementary Local–Global Optimization for Few-Shot Object Detection in Remote Sensing

Few-shot object detection (FSOD) in remote sensing remains challenging due to the scarcity of annotated samples and the complex background environments in aerial images. Existing methods often struggle to capture fine-grained local features or suffer from bias during global adaptation to novel categ...

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Bibliographic Details
Main Authors: Yutong Zhang, Xin Lyu, Xin Li, Siqi Zhou, Yiwei Fang, Chenlong Ding, Shengkai Gao, Jiale Chen
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Remote Sensing
Subjects:
few-shot learning
object detection
pseudo-label
semi-supervised learning
Online Access:https://www.mdpi.com/2072-4292/17/13/2136
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https://www.mdpi.com/2072-4292/17/13/2136

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