Understanding LeNet: A 3-Minute Overview

Understanding LeNet: A 3-Minute Overview

In this article, we present a brief overview of LeNet, a group of CNNs developed by Yann Le-Cun and others in the late 1990s.

What was LeNet?

LeNet was a group of Convolutional Neural Networks (CNNs) developed by Yann Le-Cun and others in the late 1990s. The networks were broadly considered as the first set of true convolutional neural networks. They were capable of classifying small single-channel (black and white) images, with promising results.

Were there multiple versions of LeNet?

Definitely! Chances are, if you have heard about LeNet before, you have likely only just heard about LeNet-5. This is because it was the most popular version of LeNet. However, LeNet consisted of three networks, and they were:

  1. LeNet-1 (five layers): A simple CNN.LeNet-4 (six layers): A considerable improvement over LeNet-1.LeNet-5 (seven layers): A marked improvement over LeNet-4 and the most popular.

convolution-neural-net data-science machine-learning

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