Applications
| dc.contributor.editor | Morik, Katharina | |
| dc.contributor.editor | Wietfeld, Christian | |
| dc.contributor.editor | Rahnenführer, Jörg | |
| dc.date.accessioned | 2023-01-30T17:08:53Z | |
| dc.date.available | 2023-01-30T17:08:53Z | |
| dc.date.issued | 2022 | |
| dc.identifier | ONIX_20230130_9783110785982_88 | |
| dc.identifier.uri | https://library.oapen.org/handle/20.500.12657/61130 | |
| dc.description.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. | |
| dc.language | English | |
| dc.relation.ispartofseries | De Gruyter STEM | |
| dc.subject.classification | thema EDItEUR::P Mathematics and Science::PN Chemistry | en_US |
| dc.subject.classification | thema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures | en_US |
| dc.subject.classification | thema EDItEUR::U Computing and Information Technology::UN Databases | en_US |
| dc.subject.classification | thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications | en_US |
| dc.subject.classification | thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence | en_US |
| dc.subject.other | Resource-Constrained | |
| dc.subject.other | Data Analysis | |
| dc.subject.other | Resource-Aware Machine Learning | |
| dc.subject.other | Embedded Systems and Machine Learning | |
| dc.subject.other | Big Data and Machine Learning | |
| dc.subject.other | Artificial Intelligence | |
| dc.subject.other | Highly Distributed Data | |
| dc.subject.other | ML on Small devices Data mining for Ubiquitous System Software | |
| dc.subject.other | Cyber-physical systems | |
| dc.subject.other | Machine learning in high-energy physics | |
| dc.subject.other | Machine learning for knowledge discovery | |
| dc.title | Applications | |
| dc.type | book | |
| oapen.identifier.doi | 10.1515/9783110785982 | |
| oapen.relation.isPublishedBy | 2b386f62-fc18-4108-bcf1-ade3ed4cf2f3 | |
| oapen.relation.isbn | 9783110785982 | |
| oapen.relation.isbn | 9783110785975 | |
| oapen.relation.isbn | 9783110786149 | |
| oapen.imprint | De Gruyter | |
| oapen.series.number | Volume 3 | |
| oapen.pages | 470 | |
| oapen.place.publication | Berlin/Boston |
