Deep Learning: A Survey

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Computer Vision

Deep Learning: A Survey

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

This report presents a brief survey on development of deep learning (dl) approaches, including deep neural network (dnn), convolutional neural network (cnn), recurrent neural network (rnn) including long short term memory (lstm) and gated recurrent units (gru), auto-encoder (ae), deep belief network (dbn), and generative adversarial network (gan).

In addition, we have included recent development of proposed advanced variant dltechniques based on the mentioned dl approaches.

We have also comprised recently developed frameworks, sdks, and benchmark datasets that are used for implementing and evaluating deep learning approaches.

Authors

Md Zahangir Alom, Tarek M. Taha, Christopher Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Brian C Van Esesn, Abdul A S. Awwal, Vijayan K. Asari

Related Topics

Machine learning

Deep learning approaches

Deep learning

Neural networks

Generative models

Convolutional neural network (cnn)

Auto-encoder (ae)

Generative adversarial network (gan)

Deep neural network (dnn)

Recurrent neural network (rnn)

Machine-learning approaches