IEEE

Scalable Land Cover Classification with Linear Kernel SVM on Sentinel-2 Imagery via GEE: A Case Study

Abstract: Performance evaluation of the linear kernel SVM for land cover classification using the GEE platform in Telangana, India (Longitude: 79.78E Latitude: 7.78N) is presented in this paper.
IEEE

Comparative Analysis of a Quantum SVM With an Optimized Kernel Versus Classical SVMs

Abstract: Support Vector Machine (SVM) is a widely used algorithm for classification, valued for its flexibility with kernels that effectively handle non-linear problems and high-dimensional data.
Frontiers

Identification of novel metabolism-related biomarkers of Kawasaki disease by integrating single-cell RNA sequencing analysis and machine learning algorithms

The bile acid metabolism (BAM) and fatty acid metabolism (FAM) have been implicated in Kawasaki disease (KD), but their precise mechanisms remain unclear. Identifying signature cells and genes related ...
Scientific Research Publishing

Erfani, S.M., Rajasegarar, S., Karunasekera, S. and Leckie, C. (2016) High-Dimensional and Large-Scale Anomaly Detection Using a Linear One-Class SVM with Deep Learning ...

ABSTRACT: Industrial appearance anomaly detection (AD) focuses on accurately identifying and locating abnormal regions in images. However, due to issues such as scarce abnormal samples, complex ...
GitHub

Issues: Lucid-ev/SVM-with-Linear-Kernel

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Frontiers

Predicting postoperative pulmonary infection risk in patients with diabetes using machine learning

Patients with diabetes face an increased risk of postoperative pulmonary infection (PPI). However, precise predictive models specific to this patient group are lacking. This retrospective study ...