计算机与数字工程2024，Vol.52Issue(5)：1348-1352,1372,6.DOI:10.3969/j.issn.1672-9722.2024.05.015
基于改进的YOLOv3算法的船舶目标检测
Ship Target Detection Based on Improved YOLOv3 Algorithm
摘要
Abstract
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.关键词
目标检测/YOLOv3/CIOU/ASFF/Soft-NMSKey words
target detection/YOLOv3/CIOU/ASFF/Soft-NMS分类
信息技术与安全科学引用本文复制引用
张帆,姜文刚..基于改进的YOLOv3算法的船舶目标检测[J].计算机与数字工程,2024,52(5):1348-1352,1372,6.基金项目
国家自然科学基金项目(编号:61671222)资助. （编号:61671222）
