Next-Generation Artificial Intelligence Techniques for Satellite Data Processing

14Citations
Citations of this article
23Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In this chapter, we have tried to cover majority of the artificial intelligence (AI) techniques that has contributed to the remote sensing community in the form of satellite data processing, right from the basics to advanced level. A wide variety of applications and enormous amount of satellite data growing exponentially has critical demands in speedup, cost cutting, and automation in its processing while maintaining the accuracy. We have started with the need of AI techniques and evolution made for revolutionary changes in remote sensing and other areas. Subsequently, the traditional ML techniques and its limitations, advancements, and need of introducing DL in various applications are reviewed with what is the present requisites and expectation from AI community to overcome the issues and meet the upraised demands by emerging applications. We concluded that ML and DL technology should integrate with big data technologies and cloud computing to meet the future needs.

Cite

CITATION STYLE

APA

Sisodiya, N., Dube, N., & Thakkar, P. (2020). Next-Generation Artificial Intelligence Techniques for Satellite Data Processing. In Remote Sensing and Digital Image Processing (Vol. 24, pp. 235–254). Springer. https://doi.org/10.1007/978-3-030-24178-0_11

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free