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Pytorch

Practice of implementing some CNN algorithms using Pytorch

1. Alexnet

2. VGG

3. ResNET


Data Configuration

Class = (hat, outer, top, bottom, shoes)

Train set

hat : 210

outer : 4984

top : 20218

bottom : 7304

shoes : 454


Model Version

version 1 : First version for classification

version 2 : Editing loss function and loss ratio. && Adding code for Confusion Matrix

  • I can check about data im-balance problem. Because of lack for class 1 (outer), confusion is caused between class 1 (outer) and class 2 (top)

version 3 : Adding augmentation dataset about class 1 (outer). Using validation set to training

  • ResNET not work well (maybe) because of overfitting. In case of other models, there are no great effect to total accuracy

version 4 : Adding augmentation dataset for all training dataset

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Pytorch Practice by implementing CNN models, and trying to improve performance

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