Semi-Supervised-Learning-To-Improve-Lung-Cancer-Detection:使用生成模型和半监督学习促进肺癌检测-源码

上传者: 42134051 | 上传时间: 2021-09-09 12:35:18 | 文件大小: 60.92MB | 文件类型: ZIP
半监督学习以改善肺癌的检测 使用生成模型和半监督学习促进肺癌检测 用于训练的数据集 LUNA16数据集( ) Kaggle数据科学碗2017( ) 建筑学 结果 结节检测器结果 发电机结果 分类器结果 方法 准确性 监督学习 64% 半监督学习 87.3% 资源 Kaggle数据科学碗2017内核 Luna2016-肺结节检测 Tensorflow中的半监督学习GAN [链接] DSB2017 [链接] Keras-GAN [链接] 使用很少的数据构建强大的图像分类模型[link] 贡献者: Dhamodhran( @ svella9 ) 悉达思R科蒂( siddharthkoti ) 维杰·蒙达拉吉( Vijay-Mundaragi )

文件下载

资源详情

[{"title":"( 66 个子文件 60.92MB ) Semi-Supervised-Learning-To-Improve-Lung-Cancer-Detection:使用生成模型和半监督学习促进肺癌检测-源码","children":[{"title":"Semi-Supervised-Learning-To-Improve-Lung-Cancer-Detection-master","children":[{"title":"GAN","children":[{"title":"training","children":[{"title":"wgan.py <span style='color:#111;'> 10.91KB </span>","children":null,"spread":false},{"title":"saved_model","children":[{"title":"1000_generator_epoch.hdf5 <span style='color:#111;'> 17.51MB </span>","children":null,"spread":false}],"spread":true},{"title":"GAN.py <span style='color:#111;'> 2.14KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"images","children":[{"title":"nodule2.png <span style='color:#111;'> 10.11KB </span>","children":null,"spread":false},{"title":"Architecture.PNG <span style='color:#111;'> 83.57KB </span>","children":null,"spread":false},{"title":"nodule1.png <span style='color:#111;'> 10.89KB </span>","children":null,"spread":false},{"title":"GeneratedNodules.PNG <span style='color:#111;'> 33.58KB </span>","children":null,"spread":false}],"spread":true},{"title":"Detector","children":[{"title":".gitignore <span style='color:#111;'> 7B </span>","children":null,"spread":false},{"title":"processDetectedNodules","children":[{"title":"process_unet_output.py <span style='color:#111;'> 3.62KB </span>","children":null,"spread":false}],"spread":true},{"title":"training","children":[{"title":"ROI.py <span style='color:#111;'> 7.61KB </span>","children":null,"spread":false},{"title":"saved_model","children":[{"title":"weights-improvement.hdf5 <span style='color:#111;'> 22.44MB </span>","children":null,"spread":false}],"spread":true},{"title":"Unet_Keras.py <span style='color:#111;'> 5.55KB </span>","children":null,"spread":false},{"title":"normalize_train_test.py <span style='color:#111;'> 1.10KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"README.md <span style='color:#111;'> 1.74KB </span>","children":null,"spread":false},{"title":"Data-Preprocessing","children":[{"title":"preprocessing.py <span style='color:#111;'> 5.14KB </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 6B </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"step1.cpython-36.pyc <span style='color:#111;'> 8.11KB </span>","children":null,"spread":false},{"title":"preprocessing.cpython-36.pyc <span style='color:#111;'> 4.88KB </span>","children":null,"spread":false}],"spread":true},{"title":"main.py <span style='color:#111;'> 286B </span>","children":null,"spread":false},{"title":"step1.py <span style='color:#111;'> 10.80KB </span>","children":null,"spread":false}],"spread":true},{"title":"web-app-serve","children":[{"title":".floydignore <span style='color:#111;'> 129B </span>","children":null,"spread":false},{"title":"templates","children":[{"title":"nodules.html <span style='color:#111;'> 1.74KB </span>","children":null,"spread":false},{"title":"detect.html <span style='color:#111;'> 1.80KB </span>","children":null,"spread":false},{"title":"prediction.html <span style='color:#111;'> 1.52KB </span>","children":null,"spread":false},{"title":"preprocess.html <span style='color:#111;'> 1.41KB </span>","children":null,"spread":false},{"title":"index.html <span style='color:#111;'> 2.45KB </span>","children":null,"spread":false}],"spread":true},{"title":"DataPreprocessing","children":[{"title":"preprocessing.py <span style='color:#111;'> 5.16KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"step1.cpython-36.pyc <span style='color:#111;'> 8.11KB </span>","children":null,"spread":false},{"title":"preprocessing.cpython-36.pyc <span style='color:#111;'> 4.88KB </span>","children":null,"spread":false}],"spread":true},{"title":"main.py <span style='color:#111;'> 304B </span>","children":null,"spread":false},{"title":"step1.py <span style='color:#111;'> 10.87KB </span>","children":null,"spread":false}],"spread":true},{"title":"static","children":[{"title":"js","children":[{"title":"bootstrap.bundle.min.js.map <span style='color:#111;'> 267.45KB </span>","children":null,"spread":false},{"title":"bootstrap.js <span style='color:#111;'> 112.35KB </span>","children":null,"spread":false},{"title":"bootstrap.bundle.js <span style='color:#111;'> 191.26KB </span>","children":null,"spread":false},{"title":"bootstrap.js.map <span style='color:#111;'> 190.79KB </span>","children":null,"spread":false},{"title":"bootstrap.bundle.js.map <span style='color:#111;'> 318.98KB </span>","children":null,"spread":false},{"title":"bootstrap.min.js.map <span style='color:#111;'> 158.20KB </span>","children":null,"spread":false},{"title":"bootstrap.bundle.min.js <span style='color:#111;'> 66.15KB </span>","children":null,"spread":false},{"title":"bootstrap.min.js <span style='color:#111;'> 47.80KB </span>","children":null,"spread":false}],"spread":true},{"title":"css","children":[{"title":"bootstrap-reboot.min.css.map <span style='color:#111;'> 25.27KB </span>","children":null,"spread":false},{"title":"bootstrap.css <span style='color:#111;'> 173.98KB </span>","children":null,"spread":false},{"title":"bootstrap.css.map <span style='color:#111;'> 402.00KB </span>","children":null,"spread":false},{"title":"bootstrap-reboot.css.map <span style='color:#111;'> 56.37KB </span>","children":null,"spread":false},{"title":"bootstrap-reboot.css <span style='color:#111;'> 4.69KB </span>","children":null,"spread":false},{"title":"bootstrap.min.css <span style='color:#111;'> 141.48KB </span>","children":null,"spread":false},{"title":"bootstrap-grid.css.map <span style='color:#111;'> 93.66KB </span>","children":null,"spread":false},{"title":"bootstrap-reboot.min.css <span style='color:#111;'> 3.84KB </span>","children":null,"spread":false},{"title":"bootstrap.min.css.map <span style='color:#111;'> 538.71KB </span>","children":null,"spread":false},{"title":"bootstrap-grid.min.css <span style='color:#111;'> 33.44KB </span>","children":null,"spread":false},{"title":"bootstrap-grid.css <span style='color:#111;'> 42.82KB </span>","children":null,"spread":false},{"title":"bootstrap-grid.min.css.map <span style='color:#111;'> 74.42KB </span>","children":null,"spread":false}],"spread":false}],"spread":true},{"title":"Detector","children":[{"title":"__pycache__","children":[{"title":"process_unet_output.cpython-36.pyc <span style='color:#111;'> 3.62KB </span>","children":null,"spread":false}],"spread":true},{"title":"saved_model","children":[{"title":"april04-weights-improvement.hdf5 <span style='color:#111;'> 22.44MB </span>","children":null,"spread":false}],"spread":true},{"title":"process_unet_output.py <span style='color:#111;'> 3.63KB </span>","children":null,"spread":false}],"spread":true},{"title":"floyd_requirements.txt <span style='color:#111;'> 38B </span>","children":null,"spread":false},{"title":".floydexpt <span style='color:#111;'> 85B </span>","children":null,"spread":false},{"title":"app.py <span style='color:#111;'> 5.45KB </span>","children":null,"spread":false},{"title":"Classifier","children":[{"title":"classifier.py <span style='color:#111;'> 665B </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"classifier.cpython-36.pyc <span style='color:#111;'> 840B </span>","children":null,"spread":false}],"spread":false},{"title":"saved_model","children":[{"title":"6th-fold-weights-improvement.hdf5 <span style='color:#111;'> 1.25MB </span>","children":null,"spread":false}],"spread":false}],"spread":false}],"spread":true},{"title":"Classifier","children":[{"title":"classifier.py <span style='color:#111;'> 654B </span>","children":null,"spread":false},{"title":"data_dir","children":[{"title":"non_cancer","children":[{"title":".gitignore <span style='color:#111;'> 70B </span>","children":null,"spread":false}],"spread":true},{"title":"cancer","children":[{"title":".gitignore <span style='color:#111;'> 70B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"saved_model","children":[{"title":"6th-fold-weights-improvement.hdf5 <span style='color:#111;'> 1.25MB </span>","children":null,"spread":false}],"spread":true},{"title":"classifier_train.py <span style='color:#111;'> 3.80KB </span>","children":null,"spread":false},{"title":"GAN.py <span style='color:#111;'> 2.14KB </span>","children":null,"spread":false}],"spread":true}],"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