ass日本风韵熟妇pics男人扒开女人屁屁桶到爽|扒开胸露出奶头亲吻视频|邻居少妇的诱惑|人人妻在线播放|日日摸夜夜摸狠狠摸婷婷|制服 丝袜 人妻|激情熟妇中文字幕|看黄色欧美特一级|日本av人妻系列|高潮对白av,丰满岳妇乱熟妇之荡,日本丰满熟妇乱又伦,日韩欧美一区二区三区在线

To segment crop plant seedlings accurately in natural environment, a segmentation network model based on regional semantic and edge information was presented. Firstly, the U-Net network was used as the backbone network, and the side depth supervision mechanism was used to guide the backbone network to perceive the plant edge information when extracting features. Then, based on atrous spatial pyramid pooling, the feature fusion module was built to fuse the semantic information in the backbone network and the edge information extracted by the edge perception module. The fused feature map would have enough detail information and strong semantic information. Besides, combined with the loss of edge perception and the loss of feature fusion, the joint loss function was defined for the overall network optimization. The experimental results showed that the proposed model can achieve the pixel accuracy of 0.962 and the mean intersection over union of 0.932. Compared with the U-Net, SegNet, PSPNet and DeepLabV3 models，the mean intersection over union of the used model was about 0.07 higher. Therefore, the proposed model can achieve good segmentation effect and generalization ability for crop plant seedlings in natural environment, which can provide important basis for plant location, target spraying, growth recognition and other applications.