Ship Target Detection Based on Improved YOLOv3 Algorithm
Aiming at the problems of various target scales and complex background on the water surface,this paper proposes an improved YOLOv3 algorithm.By adding the adaptive feature fusion ASFF network structure,it can effectively fuse features of dif-ferent scales and improve the detection ability of the detection network for multi-size targets.By using the CIOU loss function,the positioning accuracy of the detection frame under complex background can be improved.By using the soft non-maximum suppres-sion algorithm Soft-NMS algorithm solves the problem of erroneous deletion of target frames under multi-target overlapping.Experi-mental results show that the detection accuracy of the method proposed in this paper is better than other algorithms,and the detec-tion of small targets is improved to a certain extent.
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