LeNet-5: A Visual Guide

Interactive visual guide to LeNet-5, a neural network designed to recognize handwritten digits. It explains key components like convolution and pooling layers, feature maps, filters, and the RBF output layer, allowing users to draw a digit and observe its real-time processing through each network layer. The guide also covers SDNN sequence recognition and includes interactive visualizations for every layer.

An interactive guide to the neural network that learned to read handwritten digits. Draw a digit and watch how it moves through each layer of LeNet-5 in real time. What’s covered - Convolution and pooling layers - Feature maps and filters - RBF output layer - SDNN sequence recognition Includes interactive visualizations for every layer.