Sparse Coding for Image Classification
Implementation of sparse coding in image classification with custom MATLAB programs, including a demonstration of dictionary learning and feature extraction processes
Implementation of the ScSPM Algorithm with MATLAB Code
This package provides MATLAB implementations of the ScSPM algorithm from the CVPR 2009 paper "Linear Spatial Pyramid Matching using Sparse Coding for Image Classification." The code includes functions for sparse coding-based feature extraction and pyramid matching operations.
Probabilistic Neural Network (PNN) for Image Classification with Wavelet Processing
Implementation of image feature extraction using wavelet transforms followed by image classification through Probabilistic Neural Networks (PNN)
Matching Pursuit Algorithm
Matching Pursuit Algorithm, a classic sparse representation method widely used in face recognition, image classification, and image denoising, with growing popularity in modern applications.
Image Classification Using Neural Networks
Leveraging Neural Networks for Image Classification Tasks with Implementation Insights
Feature Extraction Using Convolutional Neural Networks
Extracting Data Features with Convolutional Neural Networks Prior to Classification
SVM for Image Classification Using Block-Based Feature Extraction
SVM for Image Classification with Block Partitioning Feature Extraction - Implementation with Technical Details
Image Classification Using BP Neural Networks
Image Classification Using BP Neural Networks
PCA-Based Image Classification Method with Implementation Insights
PCA Method for Image Classification - A Dimensionality Reduction Technique for Efficient Visual Pattern Recognition
MATLAB Implementation of K-Means Clustering Algorithm with Code Optimization Techniques
Comprehensive MATLAB implementation of K-means clustering algorithm including practical applications in image processing and data analysis with performance optimization strategies