Explainability of artificial intelligence methods, applications and challenges: A comprehensive survey

W Ding, M Abdel-Basset, H Hawash, AM Ali - Information Sciences, 2022 - Elsevier
The continuous advancement of Artificial Intelligence (AI) has been revolutionizing the
strategy of decision-making in different life domains. Regardless of this achievement, AI …

Explainability of deep vision-based autonomous driving systems: Review and challenges

É Zablocki, H Ben-Younes, P Pérez, M Cord - International Journal of …, 2022 - Springer
This survey reviews explainability methods for vision-based self-driving systems trained with
behavior cloning. The concept of explainability has several facets and the need for …

Explanations in autonomous driving: A survey

D Omeiza, H Webb, M Jirotka… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The automotive industry has witnessed an increasing level of development in the past
decades; from manufacturing manually operated vehicles to manufacturing vehicles with a …

Query-controllable video summarization

JH Huang, M Worring - … of the 2020 International Conference on …, 2020 - dl.acm.org
When video collections become huge, how to explore both within and across videos
efficiently is challenging. Video summarization is one of the ways to tackle this issue …

Deepopht: medical report generation for retinal images via deep models and visual explanation

JH Huang, CHH Yang, F Liu, M Tian… - Proceedings of the …, 2021 - openaccess.thecvf.com
In this work, we propose an AI-based method that intends to improve the conventional retinal
disease treatment procedure and help ophthalmologists increase diagnosis efficiency and …

Toward explainable artificial intelligence for early anticipation of traffic accidents

MM Karim, Y Li, R Qin - Transportation research record, 2022 - journals.sagepub.com
Traffic accident anticipation is a vital function of Automated Driving Systems (ADS) in
providing a safety-guaranteed driving experience. An accident anticipation model aims to …

Driving behavior explanation with multi-level fusion

H Ben-Younes, É Zablocki, P Pérez, M Cord - Pattern Recognition, 2022 - Elsevier
In this era of active development of autonomous vehicles, it becomes crucial to provide
driving systems with the capacity to explain their decisions. In this work, we focus on …

Energy grid management system with anomaly detection and Q-learning decision modules

JH Syu, G Srivastava, M Fojcik, R Cupek… - Computers and Electrical …, 2023 - Elsevier
Stability and security issues in energy management have become widespread research
topics, in which artificial intelligence techniques are often embedded in management …

Km4: Visual reasoning via knowledge embedding memory model with mutual modulation

W Zheng, L Yan, C Gou, FY Wang - Information Fusion, 2021 - Elsevier
Visual reasoning is a special kind of visual question answering, which is essentially multi-
step and compositional, and also requires intensive text-visual interaction. The most …

Decision-making driven by driver intelligence and environment reasoning for high-level autonomous vehicles: a survey

Y Wang, J Jiang, S Li, R Li, S Xu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Autonomous vehicle (AV) is expected to reshape the future transportation system, and its
decision-making is one of the most critical modules. Many current decision-making modules …