AlexNet

AlexNet is a convolutional neural network that won the ImageNet Large Scale Visual Recognition Challenge in 2012. It was designed by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton. The network has eight layers, five of which are convolutional layers and three are fully connected layers. It uses ReLU activation functions, dropout for regularization, and data augmentation techniques to improve performance. AlexNet significantly advanced the field of deep learning and computer vision.