Historical Context
In 1998, Yann LeCun and his team at AT&T Bell Labs introduced LeNet-5, a convolutional neural network that would lay the foundation for modern deep learning in computer vision.
The Problem: Recognizing handwritten digits for check processing
The Solution: A 7-layer convolutional neural network that could learn features automatically
The Impact: Processed millions of checks per day in real banks
Key Innovations:
• First successful CNN for real-world application
• Automatic feature learning (no hand-crafted features!)
• End-to-end trainable architecture
• Spatial hierarchy of features