13
Mar

VGG 19 is a convolutional neural network architecture that is 19 layers deep. The main purpose for which the VGG net was designed was to win the ILSVRC imagenet competition. Let’s take a brief look at the architecture of VGG19. Input: The VGG-19 takes in an image input size of 224×224.Convolutional Layers: VGG’s convolutional layers leverage a minimal receptive field, i.e., 3×3, the smallest possible size that still captures up/down and left/right. This is followed by a ReLU activation function. ReLU stands for rectified linear unit activation function, it is a piecewise linear function that will output the input if positive otherwise, the output is zero. Stride is…