The quest to open black box artificial intelligence (AI) systems evolved into an emerging
phenomenon of global interest for academia, business, and society and brought about the …

Artificial intelligence and machine learning are ubiquitous in the domain of Earth
Observation (EO) and Remote Sensing. Congruent to their success in the domain of …

The extant literature has outlined the significance of collaborative intelligence stemming
from effective partnership between artificial intelligence (AI) systems and human workers to …

Artificial Intelligence (AI) algorithms are increasingly providing decision making and
operational support across multiple domains. AI includes a wide (and growing) library of …

Some artificial intelligence algorithms have gained much attention in the rotating machinery
fault diagnosis due to their robust nonlinear regression properties. In addition, existing deep …

Multisource data fusion analysis, particularly in decision-level fusion strategies, is emerging
for application in real-life scenarios. The Dempster–Shafer evidence theory (DSET) is a …

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

In the domain of medical diagnostics, precise identification of various skin and oral diseases
is vital for effective patient care. In particular, Mpox is a potentially dangerous viral disease …

Like other Artificial Intelligence (AI) systems, Machine Learning (ML) applications cannot
explain decisions, are marred with training-caused biases, and suffer from algorithmic …

Weakly supervised target detection and semantic segmentation (WSSS) approaches aim at
learning object or pixel-level classification labels from imprecise, uncertain, or ambiguous …