DSGF-Net: A Dense-SE Gated-Fusion Architecture for High-Accuracy Small Object Detection in UAV Imagery
Source abstract
Abstract
To address the critical challenges of small object detection in UAV imagery, this paper proposes DSGF-Net (Dense-SE Gated-Fusion Network), an enhanced architecture built upon YOLOv10. It integrates a Dense SE Network (DSENet) backbone, an Adaptive Gated Fusion (AGF) module, and a Channel-Spatial Attention (CSA) mechanism. Extensive experiments on VisDrone2019-DET and CODrone demonstrate that DSGF-Net achieves substantial mAP@0.5 improvements of 5.12% and 2.36% over the YOLOv10n baseline.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Neural Network Applications · Advanced Image Fusion Techniques · Infrared Target Detection Methodologies
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