There are widespread concerns about bias and discriminatory output related to artificial
intelligence (AI), which may propagate social biases and disparities. Digital ageism refers to …

Abstract Computational Pathology (CPath) is an interdisciplinary science that augments
developments of computational approaches to analyze and model medical histopathology …

Recognition of expressions of emotions and affect from facial images is a well-studied
research problem in the fields of affective computing and computer vision with a large …

Face recognition (FR) systems have a growing effect on critical decision-making processes.
Recent works have shown that FR solutions show strong performance differences based on …

Computer Vision (CV) has achieved remarkable results, outperforming humans in several
tasks. Nonetheless, it may result in significant discrimination if not handled properly. Indeed …

Existing pruning techniques preserve deep neural networks' overall ability to make correct
predictions but could also amplify hidden biases during the compression process. We …

Deep learning has catalysed progress in tasks such as face recognition and analysis,
leading to a quick integration of technological solutions in multiple layers of our society …

The proliferation of Internet of Things (IoT) systems is having a profound impact across all
aspects of life. Recognising and identifying particular users is central to delivering the …

Given the increasing prevalence of facial analysis technology, the problem of bias in the
tools is now becoming an even greater source of concern. Several studies have highlighted …

Human-centric computer vision (HCCV) data curation practices often neglect privacy and
bias concerns, leading to dataset retractions and unfair models. HCCV datasets constructed …