AlexNet is the name of a convolutional neural network (CNN), designed by Alex Krizhevsky. AlexNet competed in the ImageNet Large Scale Visual Recognition Challenge on September 30, 2012.[4] The network achieved a top-5 error of 15.3%, more than 10.8 percentage points lower than that of the runner up.
AlexNet contained eight layers; the first five were convolutional layers, some of them followed by max-pooling layers, and the last three were fully connected layers.[3] It used the non-saturating ReLU activation function, which showed improved training performance over tanh and sigmoid
