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Deep Learning and Intelligent Robots in Government
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Author(s): Hajer Brahmi (National School of Engineers of Sfax, Tunisia) and Boudour Ammar (National School of Engineers of Sfax, Tunisia)
Copyright: 2023
Pages: 34
Source title:
Handbook of Research on Applied Artificial Intelligence and Robotics for Government Processes
Source Author(s)/Editor(s): David Valle-Cruz (Universidad Autónoma del Estado de México, Mexico), Nely Plata-Cesar (Universidad Autónoma del Estado de México, Mexico) and Jacobo Leonardo González-Ruíz (Universidad Autónoma del Estado de México, Mexico)
DOI: 10.4018/978-1-6684-5624-8.ch001
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Abstract
Deep learning algorithms have witnessed considerable advances in different sectors. Consequently, these techniques have been commonly deployed for government, mainly to support robotic and autonomous systems. They make intelligent robots, which can replace humans in danger zones or production processes and look and react like humans. The purpose of this chapter is to review the deep learning concept and particularly its applications in governments' working systems. In addition, the authors introduce the robotic field with its importance for governments. Finally, they illustrate this work by two simulated examples of robotic motions based on deep learning algorithms.
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