The AlexNet architecture is constructed using convolution neural network layers. It is made up of three fully connected layers and five convolutional layers. The first and second convolutional layers are the overlapping max pooling layers. The third, fourth and fifth layers are in direct connection and their output is given as input to the fully connected layers.
We used 64-bit operating system with Intel i7-9750H [email protected] processor, RAM of 16 GB and storage of 512 GB. We implemented this project in Python language. We used python inbuilt packages such as Tensorflow, keras to implement this program. Models required for classification and image pre-processing are imported from keras. For visualization, we are using matplotloib, seaborn library.