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- W4361761950 abstract "Single-frame infrared small target detection (SIRST) is an important topic in many fields such as target early warning, UAV detection, missile guidance and so on, and has received extensive attention recently. A segmentation based method is proposed in this paper. This network aims to solve the conflict between extracting background features and maintaining small target features. The multi-receptive field and multi-stage fusion network (MRMSNet) components a multi-receptive field module (MRM) and a multi-stage fusion module (MSM). MRM consists of two parts. It first uses multiply cascaded atrous convolution to extract multi-scale features, then exploits post-processing multi-scale features to obtain the background information. According to the characteristics of high-dimensional features and low-dimensional features, MSM performs cascaded fusion to improve the utilization of features. The results show that MRMSNet achieves better performance on SIRST datasets." @default.
- W4361761950 created "2023-04-04" @default.
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- W4361761950 date "2023-01-01" @default.
- W4361761950 modified "2023-09-27" @default.
- W4361761950 title "Multi-receptive Field and Multi-stage Fusion Network for Infrared Small Target Detection" @default.
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- W4361761950 doi "https://doi.org/10.1007/978-981-99-0923-0_63" @default.
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