U-Convnext Network for Infrared Small Target Detection

Abstract

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Due to the inherent weakness and difficulty in extracting features of infrared small targets, there is a risk of information loss in the deep layers of the network.We propose a new network model called U-Convnext. Specifically, we design a novel multi-scale Convnext module (Mcnt) based on the Convnext network, aiding in better feature extraction of infrared small targets. To mitigate deep-layer information loss, we introduce parallel dilated convolution module (Pdconv) and serial dilated convolution module (Sdconv). Pdconv captures surrounding information from multiple scales during downsampling, while Sdconv enables finer processing in the deep layers of the network. Experimental results demonstrate the superiority of the U-Convnext network over other methods.