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On this page
  • 🔢 LeNet-5
  • 👀 Visualization of the network
  • 🙌 Summary of the network
  • 🛸 AlexNet
  • 👀 Visualization of the network
  • 🔎 More Detailed
  • 🙌 Summary of the network
  • 🌱 VGG-16
  • 👀 Visualization of the network
  • 🙌 Summary of the network
  • 🔎 More Detailed
  • 😐 Drawbacks
  • 👩‍🔧 Implementation
  • 🧐 Read More

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  1. Concepts of Convolutional Neural Networks

Classic Networks

PreviousVisualizationNextOther Approaches

Last updated 4 years ago

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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

🧐 Read More

🚩
👵
Implementation of AlexNet
Detailed LeNet-5
Detailed AlexNet
Detailed VGG-16
Summary of classic networks