Diving deep in Deep Convolutional Neural Network
Divya Arora, Mehak Garg, Megha Gupta · 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN) · 2020
Artificial Neural networks have been proved most efficient in Deep Learning mainly because of large number of datasets it can handle. The most widely used is the Convolutional Neural Network (CNN). It has been proved useful for computer vision, pattern recognition and Natural Language Processing (NLP). CNN is so vastly used, as, unlike traditional Neural Nets, it reduces number of parameters and focus more on domain specific features. There are various CNN architectures proposed, such as LeNet, AlexNet, GoogleNet. In this paper, we talk about structure of CNN and all the models of CNN which are proposed till date.