A survey on artificial intelligence assurance
Artificial Intelligence (AI) algorithms are increasingly providing decision making and
operational support across multiple domains. AI includes a wide (and growing) library of …
operational support across multiple domains. AI includes a wide (and growing) library of …
Reviewing the need for explainable artificial intelligence (xAI)
The diffusion of artificial intelligence (AI) applications in organizations and society has fueled
research on explaining AI decisions. The explainable AI (xAI) field is rapidly expanding with …
research on explaining AI decisions. The explainable AI (xAI) field is rapidly expanding with …
A Contemporary Survey on Multisource Information Fusion for Smart Sustainable Cities: Emerging Trends and Persistent Challenges
The emergence of smart sustainable cities has unveiled a wealth of data sources, each
contributing to a vast array of urban applications. At the heart of managing this plethora of …
contributing to a vast array of urban applications. At the heart of managing this plethora of …
Enabling explainable fusion in deep learning with fuzzy integral neural networks
Information fusion is an essential part of numerous engineering systems and biological
functions, eg, human cognition. Fusion occurs at many levels, ranging from the low-level …
functions, eg, human cognition. Fusion occurs at many levels, ranging from the low-level …
Choquet integral based deep learning model for COVID-19 diagnosis using eXplainable AI for NG-IoT models
The COVID-19 outbreak has caused a global threat to the world healthcare system. The
virus has mutated into different variants and mutations which spread more rapidly, are more …
virus has mutated into different variants and mutations which spread more rapidly, are more …
[HTML][HTML] Representation, optimization and generation of fuzzy measures
We review recent literature on three aspects of fuzzy measures: their representations,
learning optimal fuzzy measures and random generation of various types of fuzzy measures …
learning optimal fuzzy measures and random generation of various types of fuzzy measures …
Efficient monotonicity and convexity checks for randomly sampled fuzzy measures
When dealing with a fuzzy measure on elements, verifying satisfaction of the monotonicity
conditions typically requires performing comparisons on measure values, while checking the …
conditions typically requires performing comparisons on measure values, while checking the …
On the improvement of schizophrenia detection with optical coherence tomography data using deep neural networks and aggregation functions
Schizophrenia is a serious mental disorder with a complex neurobiological background and
a well-defined psychopathological picture. Despite many efforts, a definitive disease …
a well-defined psychopathological picture. Despite many efforts, a definitive disease …
Opening the Black Box: A systematic review on explainable artificial intelligence in remote sensing
In recent years, black-box machine learning approaches have become a dominant modeling
paradigm for knowledge extraction in remote sensing. Despite the potential benefits of …
paradigm for knowledge extraction in remote sensing. Despite the potential benefits of …
Opening the Black-Box: A Systematic Review on Explainable AI in Remote Sensing
In recent years, black-box machine learning approaches have become a dominant modeling
paradigm for knowledge extraction in Remote Sensing. Despite the potential benefits of …
paradigm for knowledge extraction in Remote Sensing. Despite the potential benefits of …