Open access peer-reviewed Edited Volume

Deep Learning Applications

Edited by Pier Luigi Mazzeo

Institute of Applied Sciences and Intelligent Systems (CNR)

Co-editor:

Paolo Spagnolo

Institute of Applied Sciences and Intelligent Systems (CNR)

Deep learning is a branch of machine learning similar to artificial intelligence. The applications of deep learning vary from medical imaging to industrial quality checking, sports, and precision agriculture. This book is divided into two sections. The first section covers deep learning architectures and the second section describes the state of the art of applications based on deep learning.

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Deep Learning ApplicationsEdited by Pier Luigi Mazzeo

Published: July 14th 2021

DOI: 10.5772/intechopen.91576

ISBN: 978-1-83962-375-2

Print ISBN: 978-1-83962-374-5

eBook (PDF) ISBN: 978-1-83962-376-9

Copyright year: 2021

Books open for chapter submissions

1170 Total Chapter Downloads

1 Dimensions Citations

chaptersDownloads

Open access peer-reviewed

1. Tuning Artificial Neural Network Controller Using Particle Swarm Optimization Technique for Nonlinear System

By Sabrine Slama, Ayachi Errachdi and Mohamed Benrejeb

36

Open access peer-reviewed

2. Speech Enhancement Based on LWT and Artificial Neural Network and Using MMSE Estimate of Spectral Amplitude

By Mourad Talbi, Riadh Baazaoui and Med Salim Bouhlel

79

Open access peer-reviewed

3. The Digital Twin of an Organization by Utilizing Reinforcing Deep Learning

By Marko Kesti

120

Open access peer-reviewed

4. Deep Learning for Subtyping and Prediction of Diseases: Long-Short Term Memory

By Hayrettin Okut

146

Open access peer-reviewed

5. Modeling the Behavior of Amphiphilic Aqueous Solutions

By Gonzalo Astray Dopazo, Cecilia Martínez-Castillo, Manuel Alonso-Ferrer and Juan Carlos Mejuto

70

Open access peer-reviewed

6. The Application of Artificial Neural Network to Predicting the Drainage from Waste Rock Storages

By Liang Ma, Cheng Huang and Zhong-Sheng Liu

116

Open access peer-reviewed

7. Risk Assessment and Automated Anomaly Detection Using a Deep Learning Architecture

By Stelios C.A. Thomopoulos

127

Open access peer-reviewed

8. Application of Deep Learning Methods for Detection and Tracking of Players

By Marina Ivasic-Kos, Kristina Host and Miran Pobar

155

Open access peer-reviewed

9. Application of Artificial Neural Networks to Chemical and Process Engineering

By Fabio Machado Cavalcanti, Camila Emilia Kozonoe, Kelvin André Pacheco and Rita Maria de Brito Alves

190

Open access peer-reviewed

10. Material Classification via Machine Learning Techniques: Construction Projects Progress Monitoring

By Wesam Salah Alaloul and Abdul Hannan Qureshi

134

Edited Volume and chapters are indexed in

  • Worldcat
  • OpenAIRE
  • Google Scholar
  • AZ ebsco
  • Base
  • CNKI

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