AlexNet

Alex Krizhevsky, Ilya Sutskever, and Geoff Hinton proposed a new variant of a CNN, AlexNet, that achieved excellent performance in the 2012 ImageNet challenge. AlexNet was named after Alex Krizhevsky, the first author of the breakthrough ImageNet classification paper.

DeeplearningAI

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Initial contribute: 2020-12-05

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Google Inc
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Method-focused categoriesData-perspectiveIntelligent computation analysis

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English {{currentDetailLanguage}} English

Quoted from: https://dl.acm.org/doi/10.1145/3065386

AlexNet, which employed an 8-layer CNN, won the ImageNet Large Scale Visual Recognition Challenge 2012 by a phenomenally large margin. This network showed, for the first time, that the features obtained by learning can transcend manually-designed features, breaking the previous paradigm in computer vision.

The architectures of AlexNet and LeNet are very similar, as the following figure illustrates. Note that we provide a slightly streamlined version of AlexNet removing some of the design quirks that were needed in 2012 to make the model fit on two small GPUs.

../_images/alexnet.svg

The design philosophies of AlexNet and LeNet are very similar, but there are also significant differences. First, AlexNet is much deeper than the comparatively small LeNet5. AlexNet consists of eight layers: five convolutional layers, two fully-connected hidden layers, and one fully-connected output layer. Second, AlexNet used the ReLU instead of the sigmoid as its activation function.

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Alex Krizhevsky (2020). AlexNet, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/5e7740ac-353c-4381-a832-a2824717abdf
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Contributor(s)

Initial contribute : 2020-12-05

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Authorship

:  
Google Inc
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