Explore MATLAB source code curated for "SVM分类" with clean implementations, documentation, and examples.
MATLAB implementation for facial expression recognition combining Local Binary Pattern (LBP) and Local Phase Quantization (LPQ) algorithms, utilizing Support Vector Machine (SVM) for classification
MATLAB source code for extracting Gabor wavelet features and performing classification using Support Vector Machine (SVM) algorithm with enhanced implementation details
A robust SVM classification program capable of multi-class classification, directly executable on MATLAB platform with verified performance
Developing an SVM classifier for the iris dataset in MATLAB from scratch without using pre-built toolboxes.
This source code performs Ncut-based image segmentation while integrating feature extraction and SVM classification capabilities for comprehensive image analysis.
Implementation of SVM classification using MATLAB source code, including a sample dataset for simulation experiments with detailed algorithm explanations.
Implementation of facial expression recognition leveraging principal component analysis (PCA) and support vector machine (SVM) algorithms with direct function calls.
Complete implementation of Support Vector Machine (SVM) classification for Iris dataset in MATLAB environment, covering core mathematical derivation, optimization algorithms, and multi-class extension strategies without relying on pre-built machine learning toolboxes.
Comprehensive guide on implementing HOG feature extraction and SVM machine learning in MATLAB for computer vision applications