基于深度学习的SAR图像海洋涡旋自动检测模型
刘太龙1(), 谢涛1,2,3,4(), 李建1,3,4, 王超1,5, 张雪红1,3,4
Deep learning-based automatic detection model for ocean eddies in SAR images
LIU Tailong1(), XIE Tao1,2,3,4(), LI Jian1,3,4, WANG Chao1,5, ZHANG Xuehong1,3,4

图1. YOLOv8模型结构图

Conv代表卷积层, Concat代表拼接层, Upsample代表上采样层, Detect代表检测头, C2f代表特征融合模块, SPPF代表快速空间金字塔池化层

Fig. 1. YOLOv8 model architecture diagram. Conv represents convolutional layer, Concat represents concatenation layer, Upsample represents upsampling layer, Detect represents detection head, C2f represents Cross Stage Partial Network with 2 convolutions, and SPPF represents Spatial Pyramid Pooling Fast layer