LeNet-5 Architecture: A Pioneer in Convolutional Neural Networks
When it comes to deep learning and convolutional neural networks (CNNs), one of the most important historical milestones is Lenet 5 Architecture. Developed by Yann LeCun and his colleagues in the late 1980s, LeNet-5 was a groundbreaking model that laid the foundation for the CNNs we use today. While LeNet-5 might seem simple compared to the more complex architectures like VGG or ResNet, it has played an important role in shaping the evolution of deep learning, particularly in the field of computer vision.
In this article, we'll dive deep into the LeNet-5 architecture, its structure, and how it paved the way for modern deep learning techniques. Additionally, we’ll explore its application to deep learning regression, demonstrating how CNNs can be used beyond classification tasks.
What is LeNet-5?
LeNet-5 is a convolutional neural network architecture designed primarily for handwritten digit recognition. It was originally used to…