ImageNet Classification with Deep Convolutional Neural Networks

This paper introduces a deep convolutional neural network (CNN) architecture that achieved groundbreaking results in the ImageNet Large Scale Visual Recognition Challenge. The network's depth and architecture allowed it to learn complex image features, significantly improving image classification accuracy. This work demonstrated the power of deep learning for image recognition and has become a foundational paper in the field.