Secondly, the YOLOv3-SPP network structure is used as the basis to increase the network prediction scale to raise the small target detection performance. Then the CIoU border regression loss is introduced to improve the localization accuracy. Finally, the K-Means++ clustering algorithm is ap...
YOLOv3-SPPUWGANCIoU[K]-Means++针对水下目标检测任务中图像模糊,背景复杂以及目标小而导致误检和漏检问题,提出一种改进YOLOv3-SPP的水下目标检测算法.利用UWGAN网络对水下原始图像进行恢复,采用Mixup方法增强数据,减少错误标签记忆;以YOLOv3-SPP网络结构为基础,增加网络预测尺度,提高小目标检测性能;引入CIoU边框回归...
The experimental results show that, compared with the original YOLOv3-SPP algorithm, the improved YOLOv3-SPP military target detection algorithm has faster model convergence, with 10% higher average precision, 9% higher precision and 8% higher recall rate. With good detection ability, it can ...
无人机设备算力低下,深度模型计算量过大不适合直接部署,航拍图像目标小并且密集,模型对目标识别分类效果也不佳.为了提高深度模型航拍目标检测的精度和速度,降低计算量.对YOLOv3-SPP模型进行改进,将GIoU代替平方和用作定位损失,提高定位精度.提出了一种数据集优化和数据增强方法.再针对特定类别按照权值进行采样处理均衡...