Explainable artificial intelligence for intelligent transportation systems:
"Artificial Intelligence (AI) and Machine Learning (ML) are set to revolutionize all industries, and the Intelligent Transportation Systems (ITS) field is no exception. While ML, especially deep learning models, achieve great performance in terms of accuracy, the outcomes provided are not amena...
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton
CRC Press
2024
|
| Schlagworte: | |
| Online-Zugang: | DE-573 Volltext |
| Zusammenfassung: | "Artificial Intelligence (AI) and Machine Learning (ML) are set to revolutionize all industries, and the Intelligent Transportation Systems (ITS) field is no exception. While ML, especially deep learning models, achieve great performance in terms of accuracy, the outcomes provided are not amenable to human scrutiny and can be hardly explained. This can be very problematic especially for systems of a safety-critical nature such as transportation systems. Explainable AI methods have been proposed to tackle this issue by producing human interpretable representations of machine learning models while maintaining performance. These methods hold the potential to increase public acceptance and trust in AI-based ITS. Examining explainable AI in the field of ITS, this book has the following key features: provides the necessary background for newcomers to the field (both academics and interested partitioners). presents a timely snapshot of explainable and interpretable models in ITS applications. discusses ethical, societal, and legal implications of adopting XAI in the context of ITS. identifies future research directions and open problems"-- |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | 1 Online-Ressource (x, 275 Seiten) |
| ISBN: | 9781003324140 |
| DOI: | 10.1201/9781003324140 |
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| 520 | 3 | |a "Artificial Intelligence (AI) and Machine Learning (ML) are set to revolutionize all industries, and the Intelligent Transportation Systems (ITS) field is no exception. While ML, especially deep learning models, achieve great performance in terms of accuracy, the outcomes provided are not amenable to human scrutiny and can be hardly explained. This can be very problematic especially for systems of a safety-critical nature such as transportation systems. Explainable AI methods have been proposed to tackle this issue by producing human interpretable representations of machine learning models while maintaining performance. These methods hold the potential to increase public acceptance and trust in AI-based ITS. Examining explainable AI in the field of ITS, this book has the following key features: provides the necessary background for newcomers to the field (both academics and interested partitioners). presents a timely snapshot of explainable and interpretable models in ITS applications. discusses ethical, societal, and legal implications of adopting XAI in the context of ITS. identifies future research directions and open problems"-- | |
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Datensatz im Suchindex
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| author2 | Adadi, Amina Bouhoute, Afaf |
| author2_role | edt edt |
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| author_facet | Adadi, Amina Bouhoute, Afaf |
| building | Verbundindex |
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| dewey-full | 388.3/12 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 388 - Transportation |
| dewey-raw | 388.3/12 |
| dewey-search | 388.3/12 |
| dewey-sort | 3388.3 212 |
| dewey-tens | 380 - Commerce, communications, transportation |
| discipline | Wirtschaftswissenschaften |
| doi_str_mv | 10.1201/9781003324140 |
| format | Electronic eBook |
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| id | DE-604.BV049901789 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-06T15:06:39Z |
| institution | BVB |
| isbn | 9781003324140 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035240730 |
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| physical | 1 Online-Ressource (x, 275 Seiten) |
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| spelling | Explainable artificial intelligence for intelligent transportation systems edited by Amina Adadi, Afaf Bouhoute Explainable AI for intelligent transportation systems Boca Raton CRC Press 2024 1 Online-Ressource (x, 275 Seiten) txt rdacontent c rdamedia cr rdacarrier Includes bibliographical references and index "Artificial Intelligence (AI) and Machine Learning (ML) are set to revolutionize all industries, and the Intelligent Transportation Systems (ITS) field is no exception. While ML, especially deep learning models, achieve great performance in terms of accuracy, the outcomes provided are not amenable to human scrutiny and can be hardly explained. This can be very problematic especially for systems of a safety-critical nature such as transportation systems. Explainable AI methods have been proposed to tackle this issue by producing human interpretable representations of machine learning models while maintaining performance. These methods hold the potential to increase public acceptance and trust in AI-based ITS. Examining explainable AI in the field of ITS, this book has the following key features: provides the necessary background for newcomers to the field (both academics and interested partitioners). presents a timely snapshot of explainable and interpretable models in ITS applications. discusses ethical, societal, and legal implications of adopting XAI in the context of ITS. identifies future research directions and open problems"-- Intelligent transportation systems Artificial intelligence Artificial intelligence / (OCoLC)fst00817247 Intelligent transportation systems / (OCoLC)fst01723430 Adadi, Amina edt Bouhoute, Afaf edt Erscheint auch als Druck-Ausgabe Explainable AI for Intelligent transportation systems Boca Raton : CRC Press, 2024 pages cm 9781032344577 9781032348537 https://doi.org/10.1201/9781003324140 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Explainable artificial intelligence for intelligent transportation systems |
| title | Explainable artificial intelligence for intelligent transportation systems |
| title_alt | Explainable AI for intelligent transportation systems |
| title_auth | Explainable artificial intelligence for intelligent transportation systems |
| title_exact_search | Explainable artificial intelligence for intelligent transportation systems |
| title_full | Explainable artificial intelligence for intelligent transportation systems edited by Amina Adadi, Afaf Bouhoute |
| title_fullStr | Explainable artificial intelligence for intelligent transportation systems edited by Amina Adadi, Afaf Bouhoute |
| title_full_unstemmed | Explainable artificial intelligence for intelligent transportation systems edited by Amina Adadi, Afaf Bouhoute |
| title_short | Explainable artificial intelligence for intelligent transportation systems |
| title_sort | explainable artificial intelligence for intelligent transportation systems |
| url | https://doi.org/10.1201/9781003324140 |
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