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
Hardcover:
Available
$270.00
TOTAL SAVINGS: $270.00
Benefits
  • Printed-On-Demand (POD)
  • Usually ships one day from order
E-Book:
(Multi-User License)
Available
$243.00
List Price: $270.00
10% Discount:-$27.00
TOTAL SAVINGS: $27.00
Benefits
  • Multi-user license (no added fee)
  • Immediate access after purchase
  • No DRM
  • ePub with PDF download
Hardcover +
E-Book:
(Multi-User License)
Available
$325.00
TOTAL SAVINGS: $325.00
Benefits
  • Printed-On-Demand (POD)
  • Usually ships one day from order
  • Multi-user license (no added fee)
  • Immediate access after purchase
  • No DRM
  • ePub with PDF download
Softcover:
Available
$205.00
TOTAL SAVINGS: $205.00
Benefits
  • Printed-On-Demand (POD)
  • Usually ships one day from order
OnDemand:
(Individual Chapters)
Available
$37.50
TOTAL SAVINGS: $37.50
Benefits
  • Purchase individual chapters from this book
  • Immediate PDF download after purchase or access through your personal library
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
Table of Contents
Search this Book:
Reset
Editorial Policy
In order to ensure the highest ethical practices are achieved for each book, IGI Global provides a full document of policies and guidelines that all editors, authors, and reviewers are expected to follow. View Full Editorial Policy
Peer Review Process
The peer review process is the driving force behind all IGI Global books and journals. All IGI Global reviewers maintain the highest ethical standards and each manuscript undergoes a rigorous double-blind peer review process, which is backed by our full membership to the Committee on Publication Ethics (COPE). The full publishing process and peer review are conducted within the IGI Global eEditorial Discovery® online submission system and on average takes 30 days. Learn More
Ethics & Malpractice
IGI Global affirms that ethical publication practices are critical to the successful development of knowledge. Therefore, it is the policy of IGI Global to maintain high ethical standards in all publications. These standards pertain to all books, journals, chapters, and articles accepted for publication. This is in accordance with standard scientific principles and IGI Global’s position as a source of scientific knowledge. Learn More
Archiving
All of IGI Global's content is archived via the CLOCKSS and LOCKSS initiative. Additionally, all IGI Global published content is available in IGI Global's InfoSci® platform.