Applications

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Contributor(s)
Morik, Katharina (editor)
Wietfeld, Christian (editor)
Rahnenführer, Jörg (editor)
Language
English
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Abstract
Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications.
URI
https://library.oapen.org/handle/20.500.12657/61130
Keywords
Resource-Constrained; Data Analysis; Resource-Aware Machine Learning; Embedded Systems and Machine Learning; Big Data and Machine Learning; Artificial Intelligence; Highly Distributed Data; ML on Small devices Data mining for Ubiquitous System Software; Cyber-physical systems; Machine learning in high-energy physics; Machine learning for knowledge discovery
DOI
10.1515/9783110785982
ISBN
9783110785982, 9783110785975, 9783110786149, 9783110785982
Publisher
De Gruyter
Publisher website
https://www.degruyter.com/
Publication date and place
Berlin/Boston, 2022
Imprint
De Gruyter
Series
De Gruyter STEM, Volume 3
Classification
Chemistry
Algorithms and data structures
Databases
Computer networking and communications
Artificial intelligence
Pages
470
Rights
https://creativecommons.org/licenses/by/4.0/