fbpx

LeNet – Sem Seo 4 You

In today’s blog post, we are going to implement our first Convolutional Neural Network (CNN) — LeNet — using Python and the Keras deep learning package.

The LeNet architecture was first introduced by LeCun et al. in their 1998 paper, Gradient-Based Learning Applied to Document RecognitionAs the name of the paper suggests, the authors’ implementation of LeNet was used primarily for OCR and character recognition in documents.

The LeNet architecture is straightforward and small, (in terms of memory footprint), making it perfect for teaching the basics of CNNs — it can even run on the CPU (if your system does not have a suitable GPU), making it a great “first CNN”.

However, if you do have GPU support and can access your GPU via Keras, you will enjoy extremely fast training times (in the order of 3-10 seconds per epoch, depending on your GPU).

In the remainder of this post, I’ll be demonstrating how to implement the LeNet Convolutional Neural Network architecture using Python and Keras.

From there, I’ll show you how to train LeNet on the MNIST dataset for digit recognition.

To learn how to train your first Convolutional Neural Network, keep reading.

Looking for the source code to this post?

LeNet – Convolutional Neural Network in Python

This tutorial will be primarily code oriented and meant to help you get your feet wet with Deep Learning and Convolutional Neural Networks. Because of this intention, I am not going to spend a lot of time discussing activation functions, pooling layers, or dense/fully-connected layers — there will be plenty of tutorials on the PyImageSearch blog in the future that will cover each of these layer types/concepts in lots of detail.

Again, this tutorial is meant to be your first end-to-end example where you get to train a real-life CNN (and see it in action). We’ll get to the gory details of activation functions, pooling layers, and fully-connected layers later in this series of posts (although you should already know the basics of how convolution operations work); but in the meantime, simply follow along, enjoy the lesson, and learn how to implement your first Convolutional Neural Network with Python and Keras.

Here is a short insert of the original content, so as to spread the thoughts of the people that “Sem Seo 4 You”, considers enlightened. Content limited to 350 words.

You can read the article in its entirety, on the official website of https://www.pyimagesearch.com/2016/08/01/lenet-convolutional-neural-network-in-python/

Thanks a lot … I hope your thoughts, your geniuses can have as much resonance as possible.

You can read the article in its entirety, on the official website of https://www.pyimagesearch.com/2016/08/01/lenet-convolutional-neural-network-in-python/

Thanks a lot … I hope your thoughts, your geniuses can have as much resonance as possible.

Share on Whatsapp

Leave a Comment

Your email address will not be published. Required fields are marked *

Translate »
Enable Notifications    OK No thanks