The History Began from AlexNet: A Comprehensive Survey on Deep Learning Approaches

ArXiv  March 3, 2018
In this report researchers at the University of Dayton present a brief survey on the development of DL approaches, including Deep Neural Network, Convolutional Neural Network, Recurrent Neural Network including Long Short-Term Memory and Gated Recurrent Units, Auto-Encoder, Deep Belief Network, Generative Adversarial Network, and Deep Reinforcement Learning. DL approaches explored and evaluated in different application domains are also included in this survey. Recently developed frameworks, SDKs, and benchmark datasets that are used for implementing and evaluating deep learning approaches are included… read more. Open Access TECHNICAL ARTICLE