Support Vector Machine Optimal Algorithm for Image Segmentation
Implementing optimal Support Vector Machine algorithms for image segmentation enables effective cell separation imagery with improved precision and computational efficiency.
MATLAB Simulation of Face Age Estimation Using Support Vector Machine
MATLAB simulation implementation for facial age estimation based on Support Vector Machine (SVM) algorithm with code-level implementation details.
SVM Visualization and Plotting
Support Vector Machine plotting program that effectively visualizes different classified components with implementation details for data separation and margin representation.
Optimizing Support Vector Machine (SVM) Classification Using Particle Swarm Optimization
This article demonstrates how Particle Swarm Optimization (PSO) can enhance Support Vector Machine (SVM) classification performance through parameter tuning and optimization strategies.
Blind Equalization Algorithm Based on Support Vector Machine
A blind equalization algorithm utilizing Support Vector Machine (SVM) with QPSK (Quadrature Phase Shift Keying) as input signal, featuring MATLAB-compatible implementation considerations.
MATLAB Code Implementation for Mathematical Statistics Applications
MATLAB programs for mathematical statistics including Support Vector Machines (SVM), Gaussian Mixture Models (GMM), and other statistical algorithms with implementation details.
Support Vector Machine Package for MATLAB
A comprehensive SVM package for MATLAB with wide-ranging applications in data mining, pattern recognition, and AI, featuring robust implementations for classification and regression tasks.
Support Vector Machine Regression for Concrete Compressive Strength Prediction
Support Vector Machine (SVM) is a generalized linear classifier that performs binary classification using supervised learning, with its decision boundary defined by the maximum-margin hyperplane derived from training samples. This implementation applies SVM regression to predict concrete compressive strength, featuring verified functionality and practical code implementation.
Feature Extraction Using Gabor Wavelets for Biometric Recognition
A comprehensive MATLAB implementation for image processing using Gabor wavelet feature extraction followed by Support Vector Machine (SVM) classification, applicable to palmprint, face, and fingerprint recognition systems with detailed code implementation strategies.
Support Vector Machine Modeling for Continuous Stirred Tank Reactors: A Practical Implementation Example
This example demonstrates SVM modeling for Continuous Stirred Tank Reactors (CSTRs) in industrial processes, showcasing excellent prediction performance through regression techniques with radial basis function kernels.