计算机科学 ›› 2019, Vol. 46 ›› Issue (8): 332-336.doi: 10.11896/j.issn.1002-137X.2019.08.055
于洋, 李世杰, 陈亮, 刘韵婷
YU Yang, LI Shi-jie, CHEN Liang, LIU Yun-ting
摘要： 针对船舶图像目标检测中存在的小目标检测准确率低、系统鲁棒性差的问题,提出一种改进的YOLO v2算法对船舶图像目标进行检测。通过目标框维度聚类、网络结构改进、输入图像多尺度变换等方法对传统YOLO v2算法进行改进,使其能够更好地适应船舶目标检测任务。测试结果表明,在输入图像尺寸为416×416时,该算法的平均精确率(mean Average Precision,mAP)达到79.1%,检测速度为64帧/s(Frames Per Second,FPS)。所提方法可满足实时检测的需要,且具有小目标检测精度高、鲁棒性强的特点。
中图分类号:
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