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Can I read Challenges and Applications for Implementing Machine Learning in Computer Vision. Advances in Computer and Electrical Engineering (ACEE) Book Series on EtoBox?

Challenges and Applications for Implementing Machine Learning in Computer Vision. Advances in Computer and Electrical Engineering (ACEE) Book Series by Ramgopal Kashyap; A. V. Senthil Kumar is a nonfiction available to read on EtoBox.

What is Challenges and Applications for Implementing Machine Learning in Computer Vision. Advances in Computer and Electrical Engineering (ACEE) Book Series about?

Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. "Challenges and Applications for Implementing Machine Learning in Computer Vision" is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques

Who reads Challenges and Applications for Implementing Machine Learning in Computer Vision. Advances in Computer and Electrical Engineering (ACEE) Book Series?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Ramgopal Kashyap; A. V. Senthil Kumar
Publisher
IGI Global/Engineering Science Reference, an imprint of IGI Global
Published
2020
Language
EN
ISBN
9781522585336
Category
nonfiction
Subjects
Computer Science, Engineering, Artificial Intelligence (Ai)

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