[{"title":"( 45 个子文件 80.85MB ) 大数据驱动的深度模型在图像分类中的应用(VGG16+VGG19图像分类,源码结果都可运行)","children":[{"title":"VGG16_train_split_0.1(72 %).ipynb <span style='color:#111;'> 3.23MB </span>","children":null,"spread":false},{"title":"VGG的探索之CIFAR10分类.pdf <span style='color:#111;'> 3.91MB </span>","children":null,"spread":false},{"title":"VGG_19_whole 2.ipynb <span style='color:#111;'> 761.47KB </span>","children":null,"spread":false},{"title":"VGG16_improve_acc_last(无全连接) - 副本.ipynb <span style='color:#111;'> 3.16MB </span>","children":null,"spread":false},{"title":"img","children":[{"title":"Loss_split_0.1.png <span style='color:#111;'> 34.37KB </span>","children":null,"spread":false},{"title":"Lr_split_0.8.png <span style='color:#111;'> 9.91KB </span>","children":null,"spread":false},{"title":"Loss_split_0.01.png <span style='color:#111;'> 26.84KB </span>","children":null,"spread":false},{"title":"Acc_split_0.01.png <span style='color:#111;'> 27.16KB 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<span style='color:#111;'> 26.09KB </span>","children":null,"spread":false},{"title":"Lr_split_1.0.png <span style='color:#111;'> 10.23KB </span>","children":null,"spread":false},{"title":"Loss_split_0.5.png <span style='color:#111;'> 25.25KB </span>","children":null,"spread":false},{"title":"Acc_split_0.1.png <span style='color:#111;'> 30.14KB </span>","children":null,"spread":false},{"title":"Lr_split_0.1.png <span style='color:#111;'> 9.89KB </span>","children":null,"spread":false}],"spread":false},{"title":"VGG16_improve_acc_last(91.82 %).ipynb <span style='color:#111;'> 3.29MB </span>","children":null,"spread":false},{"title":"VGG16_train_split_0.01(36%).ipynb <span style='color:#111;'> 1.86MB </span>","children":null,"spread":false},{"title":"history","children":[{"title":"history_train_split_0.8.txt <span style='color:#111;'> 9.38KB </span>","children":null,"spread":false},{"title":"history_train_split_0.01.txt <span style='color:#111;'> 9.43KB </span>","children":null,"spread":false},{"title":"history_train_split_improve_last2.txt <span style='color:#111;'> 14.08KB </span>","children":null,"spread":false},{"title":"history_train_split_improve_last.txt <span style='color:#111;'> 13.09KB </span>","children":null,"spread":false},{"title":"history_train_split_1.0.txt <span style='color:#111;'> 7.03KB </span>","children":null,"spread":false},{"title":"history_train_split_improve2.txt <span style='color:#111;'> 13.09KB </span>","children":null,"spread":false},{"title":"history_vgg19_best.txt <span style='color:#111;'> 14.12KB </span>","children":null,"spread":false},{"title":"history_train_split_0.1.txt <span style='color:#111;'> 9.38KB </span>","children":null,"spread":false},{"title":"history_vgg19.txt <span style='color:#111;'> 4.69KB </span>","children":null,"spread":false},{"title":"history.txt <span style='color:#111;'> 6.08KB </span>","children":null,"spread":false},{"title":"history_train_split_improve.txt <span style='color:#111;'> 7.03KB </span>","children":null,"spread":false},{"title":"history_train_split_0.5.txt <span style='color:#111;'> 9.38KB </span>","children":null,"spread":false}],"spread":false},{"title":"VggNet.py <span style='color:#111;'> 2.47KB </span>","children":null,"spread":false},{"title":"vgg_19.ipynb <span style='color:#111;'> 13.63KB </span>","children":null,"spread":false},{"title":"VGG16_train_split_0.8(91.13 %).ipynb <span style='color:#111;'> 3.20MB </span>","children":null,"spread":false},{"title":"VGG16_improve_acc(92.58 %).ipynb <span style='color:#111;'> 2.52MB </span>","children":null,"spread":false},{"title":"VGG16_train_split_0.5(88 %).ipynb <span style='color:#111;'> 3.20MB </span>","children":null,"spread":false},{"title":"VGG16_train_split_1.0(92.08 %).ipynb <span style='color:#111;'> 3.18MB </span>","children":null,"spread":false},{"title":"VGG16_improve_acc2.ipynb <span style='color:#111;'> 2.71MB </span>","children":null,"spread":false},{"title":"vgg16_best.pkl <span style='color:#111;'> 58.26MB </span>","children":null,"spread":false},{"title":"VGG16_improve_acc_last2(92.68%).ipynb <span style='color:#111;'> 3.26MB </span>","children":null,"spread":false}],"spread":true}]