Explainable artificial intelligence for autonomous driving: A comprehensive overview and field guide for future research directions
Autonomous driving has achieved significant milestones in research and development over
the last decade. There is increasing interest in the field as the deployment of self-operating …
the last decade. There is increasing interest in the field as the deployment of self-operating …
A review of trustworthy and explainable artificial intelligence (xai)
The advancement of Artificial Intelligence (AI) technology has accelerated the development
of several systems that are elicited from it. This boom has made the systems vulnerable to …
of several systems that are elicited from it. This boom has made the systems vulnerable to …
End-to-end autonomous driving: Challenges and frontiers
The autonomous driving community has witnessed a rapid growth in approaches that
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …
Clip surgery for better explainability with enhancement in open-vocabulary tasks
Contrastive Language-Image Pre-training (CLIP) is a powerful multimodal large vision
model that has demonstrated significant benefits for downstream tasks, including many zero …
model that has demonstrated significant benefits for downstream tasks, including many zero …
Why did the AI make that decision? Towards an explainable artificial intelligence (XAI) for autonomous driving systems
User trust has been identified as a critical issue that is pivotal to the success of autonomous
vehicle (AV) operations where artificial intelligence (AI) is widely adopted. For such …
vehicle (AV) operations where artificial intelligence (AI) is widely adopted. For such …
Octet: Object-aware counterfactual explanations
Nowadays, deep vision models are being widely deployed in safety-critical applications, eg,
autonomous driving, and explainability of such models is becoming a pressing concern …
autonomous driving, and explainability of such models is becoming a pressing concern …
Auxiliary losses for learning generalizable concept-based models
I Sheth, S Ebrahimi Kahou - Advances in Neural …, 2024 - proceedings.neurips.cc
The increasing use of neural networks in various applications has lead to increasing
apprehensions, underscoring the necessity to understand their operations beyond mere …
apprehensions, underscoring the necessity to understand their operations beyond mere …
Goal-guided transformer-enabled reinforcement learning for efficient autonomous navigation
Despite some successful applications of goal-driven navigation, existing deep reinforcement
learning (DRL)-based approaches notoriously suffers from poor data efficiency issue. One of …
learning (DRL)-based approaches notoriously suffers from poor data efficiency issue. One of …
[HTML][HTML] Path planning algorithms in the autonomous driving system: A comprehensive review
This comprehensive review focuses on the Autonomous Driving System (ADS), which aims
to reduce human errors that are the reason for about 95% of car accidents. The ADS …
to reduce human errors that are the reason for about 95% of car accidents. The ADS …
A review of convolutional neural networks in computer vision
In computer vision, a series of exemplary advances have been made in several areas
involving image classification, semantic segmentation, object detection, and image super …
involving image classification, semantic segmentation, object detection, and image super …