December 4, 2025CAAI Transactions on Intelligence TechnologyOpen Access

Dynamic Adaptive Label Assignment for Tiny Object Detection in Remote Sensing Images

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Authors

SSShuohao ShiHarbin Normal University

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Implication

Analysis demonstrates improved detection of tiny objects in remote sensing images using a novel adaptive label assignment strategy, indicating effectiveness across datasets and object types.

Key Points

Performance improves by employing dynamic adaptive label assignment for tiny object detection in remote sensing images, enhancing overall accuracy.
Key evidence shows the proposed method effectively matches positive samples with ground truth for better detection of small objects.
Proposed strategy relies on calculating similarity distance and precise anchoring for determining label assignments within images across varying conditions.
Results from extensive experiments suggest that this method may benefit numerous applications involving satellite technology and unmanned aerial vehicles.

Cite This Study

Shuohao Shi (2025) studied this question.

synapsesocial.com/papers/6930dc78ea1aef094cca21c6 https://doi.org/10.1049/cit2.70083

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Implication

Analysis demonstrates improved detection of tiny objects in remote sensing images using a novel adaptive label assignment strategy, indicating effectiveness across datasets and object types.