Treating annotation as a data understanding problem, rather than a labeling workflow challenge, can systematically drive down error rates and reduce the time and cost of producing high-quality data ...

To identify and evaluate candidate materials, process engineers must analyze an enormous amount of data. Bulk properties like ...

Hospitals do not always have the opportunity to collect data in tidy, uniform batches. A clinic may have a handful of ...

Predicting earthquakes has long been an unattainable fantasy. Factors like odd animal behaviors that have historically been ...

This Research Topic is in collaboration with the <a href=" in FinTech and AI 2024 conference. Extended versions of work presented at the conference are welcome. <br/><br/>In today's rapidly evolving ...

A research team has mapped how machine learning is transforming the global tea industry, revealing that data-driven technologies now enhance tea cultivation, harvesting, processing, and quality ...

In a world of 8 billion people, there's one thing that makes each of us unique: our fingerprints. A variety of genetic and ...

Abstract: The spatialization of precipitation data is crucial for studies on climatology, agriculture, and climate change, as well as for urban and environmental planning. Established spatial ...

The research aim is to develop an intelligent agent for cybersecurity systems capable of detecting abnormal user behavior ...

AI-driven tools are seen to strengthened cybersecurity defenses through various ways such as anomaly detection, predictive analytics, and automated incident response, the same technologies are also ...

Abstract: Good data analysis is required for the optimal design of nuclear energy projects. However, due to financial or technical reasons, data cannot be collected regularly, which leads to missing ...