Abstract
The first remote sensing dataset that can be used for aircraft target detection is created and a 3D model simulation method for data augmentation is proposed. After statistical analysis of aircraft sizes, a high-precision improved YOLT method for target detection is proposed. YOLT is the first light algorithm focusing on target detection in remote sensing images. We improve its network structure, design a creative method based on receptive field improvement and adopt an optimized non-maximum suppression strategy. The results show that our method has better performance than other main target detection algorithms, especially for small targets and cross-scale samples.
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