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Computer Vision

ImageNet Classification with Deep Convolutional Networks

Krizhevsky, Sutskever, Hinton
Presented at CVPR 2026
Abstract

We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet contest. On the test data, we achieved top-1 and top-5 error rates substantially better than the previous state-of-the-art.

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