Abstract: Detection and prediction of the onset of seizures are among the most challenging problems in epilepsy diagnostics and treatment. Small electronic devices capable of doing that will improve ...

HOUSTON — Tech startup Unspace was founded in 2020. Since 2022, it has been advancing machine learning in the field of machine vision to improve rail safety and operational efficiency, a journey that ...

Researchers have developed a new "emotionally aware" AI-based model for classifying mental health conditions, which could ...

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...

Eight-month live online programme by CEC, IIT Roorkee equips professionals to build applied expertise across Python, machine ...

The bias problem in classification tasks and the different strategies used for bias mitigation. How these strategies are grouped into categories and a brief introduction of the most representative ...

Abstract: In this correspondence, an online sequential fuzzy extreme learning machine (OS-fuzzy-ELM) has been developed for function approximation and classification problems. The equivalence of a ...

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.

ABSTRACT: The survival of agroforestry tree species in sub-Saharan Africa is essential for sustainable livelihoods, particularly in the semi-arid environment. Drought in the Agroecological zones (AEZ) ...

Machine learning encompasses a variety of techniques tailored to solve different types of problems. Two primary categories of supervised learning are regression and classification. Regression focuses ...