Advanced fraud detection system using machine learning to identify fraudulent transactions and activities. This project implements multiple machine learning algorithms including Random Forest, XGBoost ...
Abstract: Research and development of highly accurate falling detection systems (FDSs) for individuals with medical conditions or the elderly are crucial for mitigating the risks associated with falls ...
1 Department of Environmental Sciences, Jahangirnagar University, Dhaka, Bangladesh 2 Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Lund, Sweden ...
Abstract: This paper aims to investigate the efficacy of EEG-based stress detection using a Random Forest classifier during the Stroop Test, a key psychological assessment probing cognitive functions ...
Two new advanced predictive algorithms use information about a person's health conditions and simple blood tests to accurately predict a patient's chances of having a currently undiagnosed cancer, ...
In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat 8 remote ...
@IvanNardi As per our initial discussion: Is your feature request related to a problem? Please describe. Detecting malware and covert communications within encrypted traffic, especially when ...
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