Deep Learning Methods and Applications

  • Jamil AhmadEmail author
  • Haleem Farman
  • Zahoor Jan
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)


This chapter introduces the various methods existing beneath the umbrella of deep learning paradigm, their intricate details, and their applications in various fields. Deep learning has substantially improved the predictive capacity of computing devices, due to the availability of big data, with the help of superior learning algorithms. It has made it possible as well as practical to integrate machine learning with sophisticated applications including image recognition, object detection, self-driving cars, drug discovery, and disease detection. The superior and reliable performance of deep learning methods has attracted the attention of researchers working in every field of science to utilize their strengths in order to solve problems. In addition to that, the knowledge reuse in deep learning is an interesting aspect of this technology which will also be discussed.

List of Acronyms


Convolutional neural network


Deep neural networks


Recurrent neural network


Long short-term memory


Information retrieval




Content-based image retrieval


Natural language processing


Machine learning


Multitask learning


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Copyright information

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceIslamia College PeshawarPeshawarPakistan

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