Infrared small object detection is crucial but challenging due to the diminutive size of objects and complex backgrounds in images. The proposed HCF-Net introduces modules like PPA, DASI, and MDCR to address these challenges effectively. PPA uses multi-branch feature extraction, DASI enables adaptive channel selection, and MDCR captures spatial features through multiple convolutional layers. The model is evaluated on the SIRST dataset, outperforming traditional methods with significant advantages. The network architecture includes an encoder-decoder structure with key modules strategically placed for improved performance.
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by Shibiao Xu,S... at arxiv.org 03-19-2024
https://arxiv.org/pdf/2403.10778.pdfDeeper Inquiries