In this work we have learn the study the VGG architecture and train CNN model for the classification of CIFAR-10 database based on VGG architcture.we explore the effect of the convolutional network depth on its accuracy on CIFAR-10. Our main contribution is a thorough adding droupout and batch normalization layers of networks of increase the stabiltiy of an architecture with very small (3x3) convolution filters, which shows that a significant improvement with accuracy.
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