Machine Learning and Deep Learning in Real-Time Applications

Machine Learning and Deep Learning in Real-Time Applications

Mehul Mahrishi (Swami Keshvanand Institute of Technology, India), Kamal Kant Hiran (Aalborg University, Denmark), Gaurav Meena (Central University of Rajasthan, India) and Paawan Sharma (Pandit Deendayal Petroleum University, India)
Release Date: April, 2020|Copyright: © 2020 |Pages: 344
DOI: 10.4018/978-1-7998-3095-5
ISBN13: 9781799830955|ISBN10: 1799830950|EISBN13: 9781799830979|ISBN13 Softcover: 9781799830962
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Description & Coverage
Description:

Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm.

Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.

Coverage:

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

  • Cloud Adoption
  • Computer Vision
  • Data Security
  • Embedded Systems
  • Image Processing
  • Internet of Things
  • Medical Improvements
  • Natural Language Processing
  • Smart Agriculture
  • Smart Grids
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