Explainable artificial intelligence for autonomous driving: A comprehensive overview and field guide for future research directions

S Atakishiyev, M Salameh, H Yao, R Goebel - IEEE Access, 2024 - ieeexplore.ieee.org
Autonomous driving has achieved significant milestones in research and development over
the last two decades. There is increasing interest in the field as the deployment of …

[HTML][HTML] A survey of multimodal information fusion for smart healthcare: Map** the journey from data to wisdom

T Shaik, X Tao, L Li, H **e, JD Velásquez - Information Fusion, 2024 - Elsevier
Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …

[HTML][HTML] Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation

N Díaz-Rodríguez, J Del Ser, M Coeckelbergh… - Information …, 2023 - Elsevier
Abstract Trustworthy Artificial Intelligence (AI) is based on seven technical requirements
sustained over three main pillars that should be met throughout the system's entire life cycle …

[HTML][HTML] Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions

L Longo, M Brcic, F Cabitza, J Choi, R Confalonieri… - Information …, 2024 - Elsevier
Understanding black box models has become paramount as systems based on opaque
Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response …

Emotion recognition in EEG signals using deep learning methods: A review

M Jafari, A Shoeibi, M Khodatars… - Computers in Biology …, 2023 - Elsevier
Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …

[HTML][HTML] Machine learning for advanced emission monitoring and reduction strategies in fossil fuel power plants

Z Zuo, Y Niu, J Li, H Fu, M Zhou - Applied Sciences, 2024 - mdpi.com
Fossil fuel power plants are a significant contributor to global carbon dioxide (CO2) and
nitrogen oxide (NOx) emissions. Accurate monitoring and effective reduction of these …

A perspective on explainable artificial intelligence methods: SHAP and LIME

AM Salih, Z Raisi‐Estabragh, IB Galazzo… - Advanced Intelligent …, 2025 - Wiley Online Library
eXplainable artificial intelligence (XAI) methods have emerged to convert the black box of
machine learning (ML) models into a more digestible form. These methods help to …

Toward trustworthy artificial intelligence (TAI) in the context of explainability and robustness

B Chander, C John, L Warrier… - ACM Computing …, 2024 - dl.acm.org
From the innovation, Artificial Intelligence (AI) materialized as one of the noticeable research
areas in various technologies and has almost expanded into every aspect of modern human …

Meta-learning approaches for few-shot learning: A survey of recent advances

H Gharoun, F Momenifar, F Chen… - ACM Computing …, 2024 - dl.acm.org
Despite its astounding success in learning deeper multi-dimensional data, the performance
of deep learning declines on new unseen tasks mainly due to its focus on same-distribution …

General Purpose Artificial Intelligence Systems (GPAIS): Properties, definition, taxonomy, societal implications and responsible governance

I Triguero, D Molina, J Poyatos, J Del Ser, F Herrera - Information Fusion, 2024 - Elsevier
Abstract Most applications of Artificial Intelligence (AI) are designed for a confined and
specific task. However, there are many scenarios that call for a more general AI, capable of …