Recently, a groundswell of research has identified the use of counterfactual explanations as
a potentially significant solution to the Explainable AI (XAI) problem. It is argued that (i) …

Abstract Domain adaptation deals with training models using large scale labeled data from a
specific source domain and then adapting the knowledge to certain target domains that have …

Computer vision systems today fail frequently. They also fail abruptly without warning or
explanation. Alleviating the former has been the primary focus of the community. In this work …

Earlier methods on spam filtering usually compare the contents of emails against specific
keywords, which are not robust as the spammers frequently change the terms used in …

Diagnostic and classification algorithms play an important role in data analysis, with
applications in areas such as health care, fault diagnostics, or benchmarking. Branching …

As robots aspire for long-term autonomous operations in complex dynamic environments,
the ability to reliably take mission-critical decisions in ambiguous situations becomes critical …

Case-based reasoning (CBR) has received a great deal of attention in recent years and has
established itself as a core methodology in the field of artificial intelligence. The key idea of …

Early stage diagnosis of laryngeal squamous cell carcinoma (SCC) is of primary importance
for lowering patient mortality or after treatment morbidity. Despite the challenges in …

Although digital simulations are becoming increasingly important in the industrial world
owing to the transition toward Industry 4.0, as well as the development of digital twin …

This paper introduces a methodology based on Python libraries and machine learning k-
Nearest Neighbors (KNN) algorithms to create an interactive 3D HTML model …