In recent years, deep learning (DL) has been the most popular computational approach in
the field of machine learning (ML), achieving exceptional results on a variety of complex …

This review discussed the dilemma of small data faced by materials machine learning. First,
we analyzed the limitations brought by small data. Then, the workflow of materials machine …

Ensemble learning techniques have achieved state-of-the-art performance in diverse
machine learning applications by combining the predictions from two or more base models …

Abstract Machine learning and deep learning have rapidly emerged as powerful tools in
many fields, including image and speech recognition, natural language processing, and …

Tom Freston is credited with saying ''Innovation is taking two things that exist and putting
them together in a new way''. For a long time in history, it has been the prevailing …

Human-centricity, a core value of Industry 5.0, places humans in the center of production. It
leads to the prioritization of human needs, spanning from health and safety to self …

Artificial intelligence is the driving force of change focusing on the needs and demands of
the student. The research explores Artificial Intelligence in Education (AIEd) for building …

The frequent outbreak of global infectious diseases has prompted the development of rapid
and effective diagnostic tools for the early screening of potential patients in point-of-care …

The application of Artificial Intelligence (AI) across a wide range of domains comes with both
high expectations of its benefits and dire predictions of misuse. While AI systems have …

Abstract Machine learning algorithms enable advanced decision making in contemporary
intelligent systems. Research indicates that there is a tradeoff between their model …