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AlexNet

AlexNet
Developer(s)Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton
Initial releaseJun 28, 2011
Repositorycode.google.com/archive/p/cuda-convnet/
Written inCUDA, C++
TypeConvolutional neural network
LicenseNew BSD License
AlexNet architecture and a possible modification. At the top is half of the original AlexNet, which is divided into two halves, one for each GPU. At the bottom is the same architecture, but the final "projection" layer is replaced by another that projects to fewer outputs. If one freezes the remaining model and only fine-tunes the last layer, one can obtain another vision model at a significantly lower cost than training one from scratch.
LeNet (left) and AlexNet (right) block diagram

AlexNet is a convolutional neural network architecture developed for image classification tasks, notably achieving prominence through its performance in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC). It classifies images into 1,000 distinct object categories and is regarded as the first widely recognized application of deep convolutional networks in large-scale visual recognition.

Developed in 2012 by Alex Krizhevsky in collaboration with Ilya Sutskever and his Ph.D. advisor Geoffrey Hinton at the University of Toronto, the model contains 60 million parameters and 650,000 neurons.[1] The original paper's primary result was that the depth of the model was essential for its high performance, which was computationally expensive, but made feasible due to the utilization of graphics processing units (GPUs) during training.[1]

The three formed team SuperVision and submitted AlexNet in the ImageNet Large Scale Visual Recognition Challenge on September 30, 2012.[2] The network achieved a top-5 error of 15.3%, more than 10.8 percentage points better than that of the runner-up.

The architecture influenced a large number of subsequent work in deep learning, especially in applying neural networks to computer vision.

  1. ^ a b Krizhevsky, Alex; Sutskever, Ilya; Hinton, Geoffrey E. (2017-05-24). "ImageNet classification with deep convolutional neural networks" (PDF). Communications of the ACM. 60 (6): 84–90. doi:10.1145/3065386. ISSN 0001-0782. S2CID 195908774.
  2. ^ "ImageNet Large Scale Visual Recognition Competition 2012 (ILSVRC2012)". image-net.org.

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