Unlocking Artificial Intelligence From Theory to Applications
This open access book provides a state-of-the-art overview of current machine learning research and its exploitation in various application areas. It has become apparent that the deep integration of artificial intelligence (AI) methods in products and services is essential for companies to stay comp...
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| Otros Autores: | , , |
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer Nature Switzerland
2024.
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| Edición: | 1st ed. 2024. |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009842831906719 |
Tabla de Contenidos:
- Part I: Theory
- 1. Automated Machine Learning
- 2. Sequence-Based Learning
- 3. Learning from Experience
- 4. Learning with Limited Labelled Data
- 5. The Role of Uncertainty Quantification
- 6. Process-Aware Learning
- 7. Combinatorial Optimization
- 8. Acquisition of Semantics for Machine-Learning and Deep-Learning based Applications
- Part II: Applications
- 9. Assured Resilience in Autonomous Systems
- 10. Data-driven Wireless Positioning
- 11. Comprehensible AI for Multimodal State Detection
- 12. Robust and Adaptive AI for Digital Pathology
- 13. Safe and Reliable AI for Autonomous Systems
- 14. AI for Stability Optimization in Low Voltage Direct Current Microgrids
- 15. Self-optimization in Adaptive Logistics Networks
- 16. Opitmization of Undergroud Train Systems
- 17. AI-assisted Condition Monitoring and Failure Analysis for Industrial Wireless Systems
- 18. XXL-CT Dataset Segmentation
- 19. Energy-efficient AI on the Edge.
