Explainable Artificial Intelligence for Intelligent Transportation Systems
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Explainable Artificial Intelligence for Intelligent Transportation Systems

Explainable Artificial Intelligence for Intelligent Transportation Systems


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About the Book

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.


About the Author:

Amina Adadi is an assistant professor of Computer Science at Moulay Ismail University, Morocco. She has published several papers including refereed IEEE/Springer/Elsevier journals, conference papers, and book chapters. She has served and continues to serve on executive and technical program committees of numerous international conferences such as IEEE IRASET, ESETI, WITS. Her research interests include Explainable AI, Data Efficient Models: Data Augmentation, Few-shot learning, Self-supervised learning, Transfer Learning, and Blockchain, smart contracts.

Afaf Bouhoute holds a Ph.D., a master's degree in information systems, networking and multimedia, and a bachelor's degree in computer science all from the faculty of science, Sidi Mohammed Ben Abdellah University, Fez, Morocco. She regularly serves in the technical and program committees of numerous international conferences such as ISCV, WINCOM, ICECOCS, ICDS. She also served as a co-chair of the First International Workshop on Cooperative Vehicle Networking (CVNET 2020) which was organized in conjunction with EAI ADHOCNETS 2020. Her research interests span different techniques and algorithms for modeling and analysis of driving behavior, with a focus on their application in cooperative intelligent transportation systems.


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Product Details
  • ISBN-13: 9781032344577
  • Publisher: CRC Press
  • Publisher Imprint: Crc Press
  • Height: 254 mm
  • No of Pages: 250
  • Spine Width: 18 mm
  • Width: 178 mm
  • ISBN-10: 1032344571
  • Publisher Date: 20 Oct 2023
  • Binding: Hardback
  • Language: English
  • Returnable: N
  • Weight: 761 gr


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Explainable Artificial Intelligence for Intelligent Transportation Systems
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