In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if
harnessed appropriately, may deliver the best of expectations over many application sectors …

Machine learning systems are becoming increasingly ubiquitous. These systems's adoption
has been expanding, accelerating the shift towards a more algorithmic society, meaning that …

The rising popularity of explainable artificial intelligence (XAI) to understand high-performing
black boxes raised the question of how to evaluate explanations of machine learning (ML) …

Recently, increasing attention has been drawn to the internal mechanisms of convolutional
neural networks, and the reason why the network makes specific decisions. In this paper, we …

Deep learning has recently achieved great success in many visual recognition tasks.
However, the deep neural networks (DNNs) are often perceived as black-boxes, making …

Recent transformer-based models, especially patch-based methods, have shown huge
potentiality in vision tasks. However, the split fixed-size patches divide the input features into …

Recent developments in machine learning have introduced models that approach human
performance at the cost of increased architectural complexity. Efforts to make the rationales …

Recently, a significant amount of research has been investigated on interpretation of deep
neural networks (DNNs) which are normally processed as black box models. Among the …

The field of explainable artificial intelligence (XAI) aims to uncover the inner workings of
complex deep neural models. While being crucial for safety-critical domains, XAI inherently …

Bioprinting is a relatively new and promising tissue engineering approach to solve the
problem of donor shortage for organ transplantation. It is a highly-advanced biofabrication …