posted by organizer: adadi || 1208 views || tracked by 2 users: [display]

XA2ITS 2022 : Edited Book: Explainable AI for Intelligent Transportation Systems

FacebookTwitterLinkedInGoogle

Link: https://sites.google.com/usmba.ac.ma/xa2its/
 
When Dec 31, 2022 - Dec 31, 2022
Where Taylor & Francis Group
Submission Deadline Sep 30, 2022
Notification Due Oct 31, 2022
Final Version Due Nov 15, 2022
Categories    intelligent transportation sys   explainable artificial intelli   interpretable machine learning   deep learning
 

Call For Papers

Explainable Artificial Intelligence (XAI) is an emergent research field that aims to make AI and deep models’ outcomes more human-interpretable without scarifying performance. It holds the potential to increase public acceptance and trust in systems of a safety-critical nature such as Intelligent Transportation Systems (ITS). This book focuses on XAI in the field of ITS, it aims at compiling into a coherent structure the stat-of-the-art research and development of Explainable and Trustful ITS. We are seeking chapters that propose approaches that use interpretable methods to improve the interpretability of ITS applications. Chapters addressing ethical and societal implications of XAI in ITS are also solicited.
The recommended topics include, but are not limited to the following:

-Explainable models for Autonomous driving systems
-Explainable models for Traffic management and prediction
-Explainable models for Behavioral modeling and interpretation
-Explainable models for Security, privacy and safety systems
-Explainable models for air, road, and rail traffic management
-Interpretable DNN for ITS applications
-Interpretable deep reinforcement learning, inverse reinforcement learning for ITS applications
-Inherently interpretable models by design for ITS applications
-Model -agnostic methods for ITS applications such as: SHapley Additive exPlanations (SHAP), Knowledge Graphs,
LocalInterpretable Model-Agnostic Explanations (LIME), Fuzzy logic systems…. etc.
-Safety, trust, and social acceptance enabled by interpretability
-Liability, Fairness and algorithmic accountability
-Explainability and Moral dilemma
-Explainability and Standards, laws, and regulations

Submit your papers at: https://easychair.org/conferences/?conf=xa2its
For more details, kindly refer to the book project website: https://sites.google.com/usmba.ac.ma/xa2its/
For any queries, please contact: afaf.bouhoute@usmba.ac.ma

Note: All Taylor and Francis books are submitted for indexing to indices including Web of Sciences (WOS), Scopus and other leading indexing databases

Related Resources

EAIH 2024   Explainable AI for Health
ICDM 2024   IEEE International Conference on Data Mining
EAICI 2024   Explainable AI for Cancer Imaging
SOFTFM 2024   3rd International Conference on Software Engineering Advances and Formal Methods
Cyberpunk and Digital Rebellion of AI 2024   Call for Book Chapters for the Edited Volume: Interdisciplinary Studies on German Philology: Cyberpunk and Digital Rebellion of AI
COMIT 2024   8th International Conference on Computer Science and Information Technology
ICTTE--EI 2024   2024 13th International Conference on Transportation and Traffic Engineering (ICTTE 2024)
ACML 2024   16th Asian Conference on Machine Learning
AI4SS Summer School 2024   Summer School on Artificial Intelligence for a Secure Society
IOTCB 2024   3rd International Conference on IOT, Cloud and Big Data