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Supervised Deep Learning Architectures

  • M. Arif Wani
  • Farooq Ahmad Bhat
  • Saduf Afzal
  • Asif Iqbal Khan
Chapter
Part of the Studies in Big Data book series (SBD, volume 57)

Abstract

Many supervised deep learning architectures have evolved over the last few years, achieving top scores on many tasks. Deep learning architectures can achieve high accuracy; sometimes, it can exceed human-level performance. Supervised training of convolutional neural networks, which contain many layers, is done by using a large set of labeled data. Some of the supervised CNN architectures proposed by researchers include LeNet-5, AlexNet, ZFNet, VGGNet, GoogleNet, ResNet, DenseNet, and CapsNet. These architectures are briefly discussed in this chapter.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • M. Arif Wani
    • 1
  • Farooq Ahmad Bhat
    • 2
  • Saduf Afzal
    • 3
  • Asif Iqbal Khan
    • 4
  1. 1.Department of Computer SciencesUniversity of KashmirSrinagarIndia
  2. 2.Education DepartmentGovernment of Jammu and KashmirKashmirIndia
  3. 3.Islamic University of Science and TechnologyKashmirIndia
  4. 4.Department of Computer SciencesUniversity of KashmirSrinagarIndia

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