👵Classic Networks

Network	First Usage
LeNet-5	Hand written digit classification
AlexNet	ImageNet Dataset
VGG-16	ImageNet Dataset

🔢 LeNet-5

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

👀 Visualization of the network

🙌 Summary of the network

🛸 AlexNet

• 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

👀 Visualization of the network

🔎 More Detailed

🙌 Summary of the network

🌱 VGG-16

👀 Visualization of the network

🙌 Summary of the network

🔎 More Detailed

😐 Drawbacks

• It is painfully slow to train (It has 138 million parameters 🙄)

👩‍🔧 Implementation

• Implementation of AlexNet

🧐 Read More

• Detailed LeNet-5
• Detailed AlexNet
• Detailed VGG-16
• Summary of classic networks