Yongguo Li, Yuanrong Wang, Jia Xie*, Caiyin Xu, Kun Zhang
CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 467-486, 2024, DOI:10.32604/cmc.2024.051426
Abstract To address the challenges of missed detections in water surface target detection using solely visual algorithms in unmanned surface vehicle (USV) perception, this paper proposes a method based on the fusion of visual and LiDAR point-cloud projection for water surface target detection. Firstly, the visual recognition component employs an improved YOLOv7 algorithm based on a self-built dataset for the detection of water surface targets. This algorithm modifies the original YOLOv7 architecture to a Slim-Neck structure, addressing the problem of excessive redundant information during feature extraction in the original YOLOv7 network model. Simultaneously, this modification simplifies… More >
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