AlexNet is a pioneering convolutional neural network (CNN) used primarily for image recognition and classification tasks. It won the ImageNet Large Scale Visual Recognition Challenge in 2012, marking a breakthrough in deep learning.
AlexNet is the name of a convolutional neural network (CNN) architecture, designed by Alex Krizhevsky in collaboration with Ilya Sutskever and Geoffrey ...
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AlexNet is the name of a convolutional neural network architecture, designed by Alex Krizhevsky in collaboration with Ilya Sutskever and Geoffrey Hinton, who was Krizhevsky's Ph.D. advisor at the University of Toronto.
AlexNet competed in the... Wikipedia
Creator: Alex Krizhevsky
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AlexNet is a classic convolutional neural network architecture. It consists of convolutions, max pooling and dense layers as the basic building blocks.
The AlexNet model was originally introduced in the ImageNet Classification with Deep Convolutional Neural Networks paper. The implemented architecture is ...
Jul 2, 2019 · What Now? AlexNet is an incredibly powerful model capable of achieving high accuracies on very challenging datasets. However, removing any of ...
AlexNet and ResNet-152, both have about 60M parameters but there is about a 10% difference in their top-5 accuracy. But training a ResNet-152 requires a lot of ...
Jun 24, 2022 · This was the first architecture that used GPU to boost the training performance. AlexNet consists of 5 convolution layers, 3 max-pooling layers, ...
Nov 15, 2023 · AlexNet first utilizes the dropout technique to mitigate overfitting and the ReLU activation function to avoid gradient vanishing. Therefore, we ...
First, AlexNet is much deeper than the comparatively small LeNet-5. AlexNet consists of eight layers: five convolutional layers, two fully connected hidden ...
Authors. Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton. Abstract. We trained a large, deep convolutional neural network to classify the 1.3 million ...