LeNet-5 Architecture using Python

The LeNet-5 architecture is the most widely used architecture of convolutional neural networks. It was created by Yann LeCunn in 1998. If you have never used the LeNet-5 architecture of convolutional neural networks, then this article is for you. In this article, I will take you through an introduction to the LeNet-5 Architecture and its implementation using Python.

LeNet-5 Architecture

LeNet-5 is a convolutional neural network architecture that was created by Yann LeCunn in 1998. It includes 7 layers, excluding the input layer, which contains the trainable parameters called weights. You can get a complete overview of the layers of this convolutional neural network architecture from the image below.

In the neural network architecture shown above:

  1. Layer C1 is a convolutional layer with six feature maps where the size of the feature maps is 28×28;
  2. Layer S2 is a sub-sampling layer with six feature maps where the size of the feature maps is 14×14;
  3. Layer C3 is a convolutional layer with sixteen feature maps where the size of the feature maps is 10×10;
  4. Layer S4 is s sub-sampling layer with sixteen feature maps where the size of feature maps is 5×5;
  5. Layer C5 is a convolutional layer with 120 feature maps where the size of the feature maps is 1×1;
  6. Layer F6 contains 84 units and is fully connected to the C5 convolutional layer.

I hope you now have understood the LeNet-5 architecture of convolutional neural networks. You can learn more about it from this research paper. Now in the section below, I will take you through its implementation using Python.

LeNet-5 using Python

To build the LeNet-5 convolutional neural network architecture, you can use TensorFlow and the Keras library in Python. So let’s import all the necessary Python libraries that we need to build an architecture of this neural network:

Now below is how you can build an architecture of the LeNet-5 convolutional neural network:

You can also visualize the architecture of your neural network by using the VisualKeras library in Python. If you have never used it before, then you can install it by using the pip command mentioned below:

  • pip install visualkeras

Now below is how you can visualize the architecture of your convolutional neural network:

import visualkeras
visualkeras.layered_view(model)
LeNet-5 Architecture using Python

Summary

So this is how you can build the LeNet-5 architecture of convolutional neural networks. It is an architecture of convolutional neural networks that was created by Yann LeCunn in 1998. It comprises 7 layers, excluding the input layer, which contains the trainable parameters known as weights. I hope you liked this article on an introduction to the LeNet-5 architecture and its implementation using Python. Feel free to ask your valuable questions in the comments section below.

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Aman Kharwal
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