Road-Extraction-with-ResUnet-源码

上传者: 42121412 | 上传时间: 2021-09-07 10:08:00 | 文件大小: 2.15MB | 文件类型: ZIP
基于ResUnet模型的Keras道路检测图像分割 该项目旨在借助ResUnet图像分割模型来检测和提取卫星图像中的道路。 ResUnet模型的所有代码都是用Jupyter笔记本编写的,C ++代码用于准备训练过程的数据集,一个python文件用于去除二值化蒙版中的噪声。 图书馆 凯拉斯 皮尔 脾气暴躁的 OpenCV H5py Matplotlib 模型 RESUNET是指深度残留UNET。 这是Zhengxin Zhang等人开发的编码器-解码器体系结构。 用于语义分割。 研究人员采用了它的多种应用,例如息肉分割,脑肿瘤分割,人像分割等等。 RESUNET是一个全卷积神经网络,旨在通过较少的参数获得高性能。 它是对现有UNET体系结构的改进。 RESUNET充分利用了UNET架构和Deep Residual Learning的优势。 数据集 可以通过以下链接下载数据集: :

文件下载

资源详情

[{"title":"( 31 个子文件 2.15MB ) Road-Extraction-with-ResUnet-源码","children":[{"title":"Road-Extraction-with-ResUnet-master","children":[{"title":".ipynb_checkpoints","children":[{"title":"Format_Dataset-checkpoint.ipynb <span style='color:#111;'> 5.26KB </span>","children":null,"spread":false},{"title":"ResUnet-checkpoint.ipynb <span style='color:#111;'> 45.91KB </span>","children":null,"spread":false}],"spread":true},{"title":"images","children":[{"title":"maps","children":[{"title":"val","children":[{"title":"1.jpg <span style='color:#111;'> 128.54KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"1_satellite.jpg <span style='color:#111;'> 195.98KB </span>","children":null,"spread":false},{"title":"21_pred.png <span style='color:#111;'> 23.82KB </span>","children":null,"spread":false},{"title":"9_test.png <span style='color:#111;'> 164.02KB </span>","children":null,"spread":false},{"title":"9_pred.png <span style='color:#111;'> 23.52KB </span>","children":null,"spread":false},{"title":"19_test.png <span style='color:#111;'> 154.68KB </span>","children":null,"spread":false},{"title":"79_pred.png <span style='color:#111;'> 2.43KB </span>","children":null,"spread":false},{"title":"formula.png <span style='color:#111;'> 3.86KB </span>","children":null,"spread":false},{"title":"13_test.png <span style='color:#111;'> 155.51KB </span>","children":null,"spread":false},{"title":"1.png <span style='color:#111;'> 18.71KB </span>","children":null,"spread":false},{"title":"13_pred.png <span style='color:#111;'> 24.94KB </span>","children":null,"spread":false},{"title":"74_test.png <span style='color:#111;'> 159.32KB </span>","children":null,"spread":false},{"title":"x1.png <span style='color:#111;'> 191.31KB </span>","children":null,"spread":false},{"title":"21_test.png <span style='color:#111;'> 164.38KB </span>","children":null,"spread":false},{"title":"44_pred.png <span style='color:#111;'> 21.27KB </span>","children":null,"spread":false},{"title":"19_pred.png <span style='color:#111;'> 16.99KB </span>","children":null,"spread":false},{"title":"79_test.png <span style='color:#111;'> 117.21KB </span>","children":null,"spread":false},{"title":"1_computer.jpg <span style='color:#111;'> 74.39KB </span>","children":null,"spread":false},{"title":"dice_coefficient.png <span style='color:#111;'> 16.85KB </span>","children":null,"spread":false},{"title":"44_test.png <span style='color:#111;'> 166.28KB </span>","children":null,"spread":false},{"title":"74_pred.png <span style='color:#111;'> 23.11KB </span>","children":null,"spread":false}],"spread":false},{"title":"splitter","children":[{"title":"main.cpp <span style='color:#111;'> 1.63KB </span>","children":null,"spread":false},{"title":"main <span style='color:#111;'> 673.10KB </span>","children":null,"spread":false}],"spread":true},{"title":"thresholder","children":[{"title":"main.cpp <span style='color:#111;'> 1.26KB </span>","children":null,"spread":false},{"title":"main <span style='color:#111;'> 511.73KB </span>","children":null,"spread":false}],"spread":true},{"title":"filter.py <span style='color:#111;'> 592B </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 3.39KB </span>","children":null,"spread":false},{"title":"ResUnet.ipynb <span style='color:#111;'> 45.91KB </span>","children":null,"spread":false},{"title":"Format_Dataset.ipynb <span style='color:#111;'> 2.90KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明