Google's Inception-v3 model consists of multiple convolutional kernels that vary in multiple sizes. Each of these convolutional kernels identifies features for each dimension for each scale. This model adopts a form of residual network that makes use of skip connections. Residual networks take the input data and add it to the output, Thus enabling ad forcing the network to predict the residual input rather than the expected output. \cite{networks}