Comparison of the LeNet and AlexNet convolution, pooling, and dense layers
(AlexNet image size should be 227x227x3, instead of 224x224x3, so the math will come out right. The original paper said different numbers, but Andrej Karpathy, the head of computer vision at Tesla, said it should be 227x227x3 (he said Alex didn't describe why he put 224x224x3). The next convolution should be 11x11 with stride 4: 55x55x96 (instead of 54x54x96). It would be calculated, for example, as: [(input width 227 - kernel width 11) / stride 4] + 1 = [(227 - 11) / 4] + 1 = 55. Since the kernel output is the same length as width, its area is 55x55.)