Using Deep Learning in Image Classification

In our daily life the computer and technology took almost all aspects of life through the use of smartphones, smartwatch, laptops, internet, and so many different tools. This makes people around the globe utilize services and tools more than before which lead to introduce hundreds of algorithms to enhance such services. The deep learning tools in AI become an urgent need to simulate a human behavior by the machine as both consists of neurons, and a weighted input to that neurons. The trip from a single neuron to AlexNet and then to EfficientNet will predict a bright future of this area in AI especially with dealing with images. Computer vision considered as mid-way that collect both AI and image processing to gather to perform a classification of images through AI to increase the understandability of such images and give the ability for machine for better decision making upon these images without human interfere, this article provides a survey study about a number of most recent papers about techniques AlexNet, ResNet, GoogLeNet, VGG, MobileNet, DenseNet, LetNet, Gabor CNN, Siamese CNN, PPF CNN and 3D GAN, and summarize there efficiency and weak points according to the papers so to we can provide a good guide for this area researchers.