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October 19, 2025Open Access

RS-TinyNet: Stage-wise Feature Fusion Network for Detecting Tiny Objects in Remote Sensing Images

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Proposed model enhances tiny object detection in remote sensing images, indicating improved accuracy and feature integration.

RS-TinyNet improves tiny object detection by 4.0% AP and 6.5% AP75 using a specialized feature fusion approach.
The model features multi-dimensional collaborative attention to strengthen saliency and enhance detection capabilities.
Incorporating tiny object saliency modeling and feature integrity reconstruction advances detection in complex imagery settings.
Extensive evaluations confirm RS-TinyNet's effectiveness across diverse remote sensing datasets like AI-TOD and DIOR.

Jiang et al. (2025) studied this question.

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October 19, 2025Open Access

View Full Paper

Ask AI

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Authors

Proposed model enhances tiny object detection in remote sensing images, indicating improved accuracy and feature integration.

RS-TinyNet improves tiny object detection by 4.0% AP and 6.5% AP75 using a specialized feature fusion approach.
The model features multi-dimensional collaborative attention to strengthen saliency and enhance detection capabilities.
Incorporating tiny object saliency modeling and feature integrity reconstruction advances detection in complex imagery settings.
Extensive evaluations confirm RS-TinyNet's effectiveness across diverse remote sensing datasets like AI-TOD and DIOR.

Jiang et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark