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This repository contains the source code of our work on designing efficient CNNs for computer vision

VGG 19 is a Very Deep Convolutional Networks for Large-Scale Image Recognition In this work we investigate the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting. Our main contribution is a thorough evaluation of networks of increasing depth using an architecture with very small (3x3) convolution filters, which shows that a significant improvement on the prior-art configurations can be achieved by pushing the depth to 16-19 weight layers.We use the network with pretrained parameters to classify images on ImageNet.