Old CNN for handwritten base-10 digit classification, by a team led by Yann LeCun at AT&T Bell Labs. See this page.
Architecture
Seven total layers: 2 convolutional layers, 2 pooling layers, and 3 fully-connected layers.
In sequential order:
- Input image is in grayscale, so a single input channel into the first convolutional layer.
- Convolutional layer has 6 output channels, into ReLU and 2D average pooling.
- Next convolutional layer has 16 output channels.
- After ReLU and 2D average pooling, there’s 2 fully connected layers.
Implementation
In PyTorch, we can succinctly implement the architecture as follows.