AIMC Topic: Support Vector Machine

Clear Filters Showing 291 to 300 of 4702 articles

Spatiotemporal analysis of land surface temperature and land cover changes in Prešov city using downscaling approach and machine learning algorithms.

Environmental monitoring and assessment
In recent decades, global climate change and rapid urbanization have aggravated the urban heat island (UHI) effect, affecting the well-being of urban citizens. Although this significant phenomenon is more pronounced in larger metropolitan areas due t...

SVM directed machine learning classifier for human action recognition network.

Scientific reports
Understanding human behavior and human action recognition are both essential components of effective surveillance video analysis for the purpose of guaranteeing public safety. However, existing approaches such as three-dimensional convolutional neura...

Characterizing Chinese saffron Origin, Age and grade using VNlR hyperspectral imaging and Machine learning.

Food research international (Ottawa, Ont.)
Saffron (Crocus sativus L.), the dried stigma, is an extremely valuable spice and medicinal herb, whose economic value is affected by geographical origin, age and grade. In this study, we proposed a method to identify saffron from different Chinese o...

Machine learning driven benchtop Vis/NIR spectroscopy for online detection of hybrid citrus quality.

Food research international (Ottawa, Ont.)
The aim of this study was to explore application of visible and near-infrared (Vis/NIR) spectroscopy combined with machine learning models for SSC and TA prediction of hybrid citrus. The Vis/NIR spectra of samples including navel-region, equator-regi...

Utilizing integrated bioinformatics and machine learning approaches to elucidate biomarkers linking sepsis to purine metabolism-associated genes.

Scientific reports
Sepsis, characterized as a systemic inflammatory response triggered by pathogen invasion, represents a continuum that may progress from mild systemic infection to severe sepsis, potentially culminating in septic shock and multiple organ dysfunction s...

Predicting noncontact injuries of professional football players using machine learning.

PloS one
Noncontact injuries are prevalent among professional football players. Yet, most research on this topic is retrospective, focusing solely on statistical correlations between Global Positioning System (GPS) metrics and injury occurrence, overlooking t...

Feature efficiency in IoMT security: A comprehensive framework for threat detection with DNN and ML.

Computers in biology and medicine
BACKGROUND: To address critical security challenges in the Internet of Medical Things (IoMT), this study develops a feature selection framework to improve detection accuracy and computational efficiency in IoMT cybersecurity. By optimizing feature se...

Vision Sensor for Automatic Recognition of Human Activities via Hybrid Features and Multi-Class Support Vector Machine.

Sensors (Basel, Switzerland)
Over recent years, automated Human Activity Recognition (HAR) has been an area of concern for many researchers due to its widespread application in surveillance systems, healthcare environments, and many more. This has led researchers to develop cohe...

Assessing the environmental determinants of micropollutant contamination in streams using explainable machine learning and network analysis.

Chemosphere
Even at trace concentrations, micropollutants, including pesticides and pharmaceuticals, pose considerable ecological risks, and the increasing presence of synthetic chemical substances in aquatic systems has emerged as a growing concern. Moreover, l...

Virtual reality-assisted prediction of adult ADHD based on eye tracking, EEG, actigraphy and behavioral indices: a machine learning analysis of independent training and test samples.

Translational psychiatry
Given the heterogeneous nature of attention-deficit/hyperactivity disorder (ADHD) and the absence of established biomarkers, accurate diagnosis and effective treatment remain a challenge in clinical practice. This study investigates the predictive ut...