Six machine learning algorithms—k-nearest neighbors, naive Bayes, multilayer perceptron, random forest, support vector machine, and Extreme Gradient Boosting (XGBoost)—were developed using 10-fold ...

Abstract: Learning a classifier from ambiguously labeled face images is challenging since training images are not always explicitly-labeled. For instance, face images of two persons in a news photo ...

Abstract: The large number of visual applications in multimedia sharing websites and social networks contribute to the increasing amounts of multimedia data in cyberspace. Video data is a rich source ...

After the brutal Oct. 7, 2023, attack by Hamas, the Israel Defense Forces deluged Gaza with bombs, drawing on a database painstakingly compiled through the years that detailed home addresses, tunnels ...

In agriculture sector, machine learning has been widely used by researchers for crop yield prediction. However, it is quite difficult to identify the most critical features from a dataset. Feature ...

Objective: Based on machine learning (ML) methods, this study aimed to develop and validate a stable and scalable panel of cognitive tests for the early detection of MCI and dementia based on the ...

Automation, algorithms and machine learning are taking over recruitment and hiring. How do we compete with the rise of robots? Laura is a professional nitpicker and good-humored troubleshooter with ...

Background: Aortic dissection (AD) is a life-threatening disease. Chromatin regulators (CRs) are indispensable epigenetic regulators. We aimed to identify differentially expressed chromatin regulators ...