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Road_extraction:注意Unet和DeepUnet实现,用于道路提取多gpu张量流-源码

上传者: weixin_42172972 | 上传时间:2023/1/22 22:31:45 | 文件大小:16.51MB | 文件类型:ZIP
Road_extraction:注意Unet和DeepUnet实现,用于道路提取多gpu张量流-源码
Road_extraction使用多GPU模型张量流的AttentionUnet和DeepUnet实现道路提取DeepU-Net的多种变体已经过额外的层和额外的卷积测试。
尽管如此,优于所有人的模型是AttentionU-Net:学习在哪里寻找胰腺。
我添加了一个额外的调整来提高功能,将卷积块切换为残差块TensorFlow分割TF细分模型,U-Net,AttentionUnet,DeepU-Net(U-Net的所有变体)使用神经网络(NN)进行图像分割,旨在从遥感影像中提取道路网络,它可用于其他应用中,标记图像中的每个像素(语义分割)可以在以下论文中找到详细信息:注意U-Net附加模块要求Python3.6CUDA10.0TensorFlow1.9Keras2.0模组utils.py和helper.py函数用于预处理数据并保存。
本软件ID:15365818

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