Sensation of Deep Learning in Image Processing Applications

View Sample PDF

Author(s): Ramgopal Kashyap (Amity University, Raipur, India)
Copyright: 2019
Pages: 25
Source title: Handbook of Research on Deep Learning Innovations and Trends
Source Author(s)/Editor(s): Aboul Ella Hassanien (Cairo University, Egypt), Ashraf Darwish (Helwan University, Egypt)and Chiranji Lal Chowdhary (VIT University, India)
DOI: 10.4018/978-1-5225-7862-8.ch005

Keywords: Artificial Intelligence / Computer Science & IT / Engineering Science Reference / Neural Networks

Purchase

View Sensation of Deep Learning in Image Processing Applications on the publisher's website for pricing and purchasing information.

Abstract

This chapter will address challenges with IoT and machine learning including how a portion of the difficulties of deep learning executions while planning the arrangement and choice of right calculation. Existing research in deep learning and IoT was focused to find how garbage in will deliver waste out, which is exceptionally appropriate for the scope of the informational index for machine learning. The quality, sum, readiness, and choice of information are essential to the achievement of a machine learning arrangement. Consequently, this chapter aims to provide an overview of how the system can use technologies along with deep learning and challenges to realize the security challenges IoT can support. Even though calculations can work in any nonexclusive conditions, there are particular rules to determine which calculation would work best under which circumstances. How reinforcement learning deep learning is useful for IoT will also be covered in the chapter.

The IRMA Community

Research IRM

Sensation of Deep Learning in Image Processing Applications

Purchase

Abstract

Related Content

IRMA Sponsors