期刊论文

Water surface garbage detection based on improved YOLOv5s

中文

武汉轻工大学学报

2095-7386

2023

42

5

98-105+113

10.3969/j.issn.2095-7386.2023.05.014

国家自然科学基金(61906140)。

本校为第一机构

针对传统水面垃圾检测方法在水面环境复杂的情况下难以兼顾检测精度和检测速度以及检测效率低的问题,提出一种改进YOLOv5s的水面垃圾检测方法。首先使用GhostBottleneck模块替换YOLOv5s模型结构中的C3和部...展开更多 针对传统水面垃圾检测方法在水面环境复杂的情况下难以兼顾检测精度和检测速度以及检测效率低的问题,提出一种改进YOLOv5s的水面垃圾检测方法。首先使用GhostBottleneck模块替换YOLOv5s模型结构中的C3和部分CBS模块,使YOLOv5s模型更加轻量化,提升检测效率;然后在骨干网络的末端加入ECA注意力机制,让模型对水面垃圾的特征提取有更多关注;再使用Alpha-CIOU损失函数代替YOLOv5原本的...

Addressing the challenges faced by conventional water surface garbage detection techniques in reconciling detection accuracy and speed,as well as the low detection efficiency in intricate aquatic environments,we present an enhanced water surface garbage detection approa...MORE Addressing the challenges faced by conventional water surface garbage detection techniques in reconciling detection accuracy and speed,as well as the low detection efficiency in intricate aquatic environments,we present an enhanced water surface garbage detection approach founded on the YOLOv5s framework.Initially,the Gh...