Examining the Impact of Deep Learning and IoT on Multi-Industry Applications
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Examining the Impact of Deep Learning and IoT on Multi-Industry Applications

Roshani Raut (Pimpri Chinchwad College of Engineering (PCCOE), Pune, India) and Albena Dimitrova Mihovska (CTIF Global Capsule (CGC), Denmark)
Release Date: January, 2021|Copyright: © 2021 |Pages: 304|DOI: 10.4018/978-1-7998-7511-6
ISBN13: 9781799875116|ISBN10: 1799875113|EISBN13: 9781799875178|ISBN13 Softcover: 9781799883586
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Description

Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings.

Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers’ points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • ADHD Diagnosis
  • Agriculture Applications
  • Artificial Intelligence
  • Cancer Diagnosis
  • Computer Vision
  • COVID-19
  • Cyber Security
  • Deep Learning
  • Fog Networks
  • Healthcare Applications
  • Internet of Things (IoT)
  • Irrigation System
  • Machine Learning
  • Medical Diagnosis
  • Neuroimaging
  • Object Detection and Tracking
  • Semantic Sentiment Analysis
  • Smart Devices
  • Social Media

Table of Contents and List of Contributors

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