Deep learning (DL) has been widely used in various fields. However, its black-box nature
limits people's understanding and trust in its decision-making process. Therefore, it becomes …

Artificial intelligence, and especially deep neural networks, have evolved substantially in the
recent years, infiltrating numerous domains of applications, often greatly impactful to …

This paper addresses various issues in the literature concerning adversarial attack detection
in Vehicular Ad-hoc Networks (VANETs). These issues include the failure to consider both …

Deep Learning (DL) has gained enormous popularity recently; however, it is an opaque
technique that is regarded as a black box. To ensure the validity of the model's prediction, it …

Abstract While Explainable Artificial Intelligence (XAI) techniques have been widely studied
to explain predictions made by deep neural networks, the way to evaluate the faithfulness of …

Abstract Local Interpretable Model-agnostic Explanations (LIME)-a widely used post-ad-hoc
model agnostic explainable AI (XAI) technique. It works by training a simple transparent …

Highlights•Body size automatic measurement based on beef cattle point clouds was
achieved.•Twelve micro-pose features were defined to describe beef cattle postures.•The …

The majority of eXplainable Artificial Intelligence (XAI) methods assume the local linearity of
the decision boundary, leading to significant errors when dealing with non-linear local …

Deep learning models have revolutionized numerous fields, yet their decision-making
processes often remain opaque, earning them the characterization of “black-box” models …

LIME has gained significant attention as an explainable artificial intelligence algorithm that
sheds light on how complex machine learning models make decisions within a specific …