AdaBoost-Based Face Recognition System
A comprehensive face recognition program implementing the AdaBoost algorithm, including technical documentation and user manual with code implementation details
Adaboost Algorithm: Constructing Strong Classifiers from Weak Classifiers
Implementation of Adaboost algorithm combining weak classifiers into strong classifiers with visualization and analysis of sample size impact on performance
Face Recognition System Based on MATLAB R2008
A face recognition system developed using MATLAB R2008 that implements two distinct algorithms: PCA+Adaboost and PCA+SVM, utilizing the ORL face database. The system achieves 84% recognition accuracy by processing a single facial image to identify individuals, demonstrating efficient feature extraction and classification through principal component analysis combined with ensemble learning and support vector machine methods.
MATLAB Implementation of AdaBoost-Based Face Detection Algorithm
This project provides a MATLAB implementation of a face detection algorithm utilizing the AdaBoost method, offering valuable insights for developers working on computer vision applications with feature selection and classifier training processes.
Adaboost Face Recognition: MATLAB Implementation with Machine Learning Algorithms
MATLAB source code for face recognition using Adaboost algorithm, featuring comprehensive face detection implementation with weak classifier combination and feature selection techniques
AdaBoost-based Face Detection Algorithm
Face detection algorithm utilizing AdaBoost methodology, featuring complete training pipeline with optimized data reading structure to reduce memory consumption
AdaBoost Face Detection DLL Module using OpenCV with MATLAB Integration
This MATLAB-based implementation utilizes an OpenCV-built AdaBoost face detection DLL module to perform real-time face detection on video streams captured from USB cameras. The system displays detection results in real-time, though with slightly lower performance compared to native C implementations. After downloading, users can run the module directly in MATLAB without modifying relative file positions within the folder structure.
Boosting Algorithm: Adaboost Implementation and Theory
Adaboost Algorithm with MATLAB Implementation - An iterative machine learning method that trains multiple weak classifiers on the same dataset and combines them into a powerful ensemble classifier through weighted voting mechanisms.
AdaBoost Algorithm for Beginners
A comprehensive introduction to AdaBoost for machine learning beginners with code implementation insights
Comparative Analysis of SVM and AdaBoost Algorithms for Target Recognition
An article comparing SVM and AdaBoost algorithms, implementing both methods for target recognition with detailed performance evaluation and code implementation insights.