Convolutional Neural Network 2
Q1. Sparse Connection What does sparsity of connections mean as a benefit of using convolutional layers? Choose the correct answer from below: A. Each filter is connected to every channel in the previous layer B. Each layer in a convolutional network is connected only to two other layers C. Each activation in the next layer depends on only a small number of activations from the previous layer D. Regularization causes gradient descent to set many of the parameters to zero Ans: C Correct answer: Each activation in the next layer depends on only a small number of activations from the previous layer. Reason : In neural network usage, “dense” connections connect all inputs. By contrast, a CNN is “sparse” because only the local “patch” of pixels is connected, instead using all pixels as an input. High correlation can be...