Face Recognition Using Hidden Markov Models
Hidden Markov Model (HMM)-based face recognition achieves an impressive 90% accuracy rate through probabilistic pattern analysis and sequential feature processing.
Explore MATLAB source code curated for "隐马尔可夫模型" with clean implementations, documentation, and examples.
Hidden Markov Model (HMM)-based face recognition achieves an impressive 90% accuracy rate through probabilistic pattern analysis and sequential feature processing.
MATLAB implementation of HMM (Hidden Markov Model) algorithms including parameter estimation and sequence decoding
Implementation of a Chinese speech recognition system using Continuous Density Hidden Markov Models (CD-HMM) in MATLAB environment with code-level implementation details.
Wavelet-domain Hidden Markov Model-based image denoising represents the highest-performing image denoising methodology currently available, combining multiscale signal analysis with statistical modeling techniques.
Implementation of Speech Modeling using Hidden Markov Models - A Statistical Modeling Approach
Complete MATLAB implementation of Hidden Markov Models (HMM) including core algorithms and practical applications with detailed code-related descriptions
Hidden Markov Model Toolbox for MATLAB with Code Implementation Features
Hidden Markov Model Toolbox for Sequence Data Analysis