Titlebook: Deep Learning for Unmanned Systems; Anis Koubaa,Ahmad Taher Azar Book 2021 The Editor(s) (if applicable) and The Author(s), under exclusiv

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Marken, Variablen, Querverweise,easibility of the proposed models, together with the energy and cost savings attained. Results demonstrate that Deep Q-Learning based algorithms represent a viable and economically convenient solution for enabling energy self-sustainability of mobile networks grouped in micro-grids.

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Deep Learning for Unmanned Systems978-3-030-77939-9Series ISSN 1860-949X Series E-ISSN 1860-9503

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https://doi.org/10.1007/978-1-4612-2802-8ous systems with the ability to automatically learn underlying features in data at different levels of abstractions, to build complex concepts out of simpler ones and to get better with experience without being explicitly programmed. This book chapter provides a comprehensive review on the applicati

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Desk Reference for Neurosciencetill depends on a remote human controller with robust wireless links to perform several of these applications. The lack of autonomy restricts the domains of application and tasks for which a UAS can be deployed. This is even more relevant in tactical and rescue scenarios where the UAS needs to opera

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