π΅Classic Networks
Last updated
Last updated
LeNet-5 is a very simple network - By modern standards -. It only has 7 layers;
among which there are 3 convolutional layers (C1, C3 and C5)
2 sub-sampling (pooling) layers (S2 and S4)
1 fully connected layer (F6)
Output layer
Too similar to LeNet-5
It has more filters per layer
It uses ReLU instead of tanh
SGD with momentum
Uses dropout instead of regularaization
It is painfully slow to train (It has 138 million parameters π)
Network
First Usage
LeNet-5
Hand written digit classification
AlexNet
ImageNet Dataset
VGG-16
ImageNet Dataset