[HTML][HTML] Notions of explainability and evaluation approaches for explainable artificial intelligence
Abstract Explainable Artificial Intelligence (XAI) has experienced a significant growth over
the last few years. This is due to the widespread application of machine learning, particularly …
the last few years. This is due to the widespread application of machine learning, particularly …
Explainable artificial intelligence: a systematic review
Explainable Artificial Intelligence (XAI) has experienced a significant growth over the last few
years. This is due to the widespread application of machine learning, particularly deep …
years. This is due to the widespread application of machine learning, particularly deep …
Classification of explainable artificial intelligence methods through their output formats
Machine and deep learning have proven their utility to generate data-driven models with
high accuracy and precision. However, their non-linear, complex structures are often difficult …
high accuracy and precision. However, their non-linear, complex structures are often difficult …
Clinical interpretable deep learning model for glaucoma diagnosis
Despite the potential to revolutionise disease diagnosis by performing data-driven
classification, clinical interpretability of ConvNet remains challenging. In this paper, a novel …
classification, clinical interpretability of ConvNet remains challenging. In this paper, a novel …
A new perspective on evaluation methods for explainable artificial intelligence (xai)
One of the big challenges in the field of explainable artificial intelligence (XAI) is how to
evaluate explainability approaches. Many evaluation methods (EMs) have been proposed …
evaluate explainability approaches. Many evaluation methods (EMs) have been proposed …
Learning to act properly: Predicting and explaining affordances from images
We address the problem of affordance reasoning in diverse scenes that appear in the real
world. Affordances relate the agent's actions to their effects when taken on the surrounding …
world. Affordances relate the agent's actions to their effects when taken on the surrounding …
Generating explanations for embodied action decision from visual observation
Getting trust is crucial for embodied agents (such as robots and autonomous vehicles) to
collaborate with human beings, especially non-experts. The most direct way for mutual …
collaborate with human beings, especially non-experts. The most direct way for mutual …
Multimodal explainable artificial intelligence: A comprehensive review of methodological advances and future research directions
N Rodis, C Sardianos, GT Papadopoulos… - arXiv preprint arXiv …, 2023 - arxiv.org
The current study focuses on systematically analyzing the recent advances in the field of
Multimodal eXplainable Artificial Intelligence (MXAI). In particular, the relevant primary …
Multimodal eXplainable Artificial Intelligence (MXAI). In particular, the relevant primary …
Regional multi-scale approach for visually pleasing explanations of deep neural networks
Recently, many methods to interpret and visualize deep neural network predictions have
been proposed, and significant progress has been made. However, a more class …
been proposed, and significant progress has been made. However, a more class …
Explainable AI: to reveal the logic of black-box models
Chinu, U Bansal - New Generation Computing, 2024 - Springer
Artificial intelligence (AI) is continuously evolving; however, in the last 10 years, it has gotten
considerably more difficult to explain AI models. With the help of explanations, end users …
considerably more difficult to explain AI models. With the help of explanations, end users …