Explore MATLAB source code curated for "识别" with clean implementations, documentation, and examples.
A comprehensive workflow for license plate character recognition system, encompassing license plate localization, character segmentation, and character recognition processes with algorithmic implementations.
MATLAB implementation of Fuzzy C-Means clustering, a fuzzy mathematics-based clustering method for image segmentation. This approach enables cluster analysis results for image analysis and recognition applications, with practical code examples demonstrating centroid initialization and membership function calculations.
Implementing MATLAB neural network algorithms for personality recognition in images through neural network training, enabling gender identification (male/female) from facial features with implementation insights on network architecture and training processes.
Finger vein recognition code consisting of preprocessing and recognition modules, including annotated images and MATLAB scripts with detailed explanations of algorithms and key functions
Adaptive Resonance Theory Networks demonstrate exceptional performance in pattern classification and associative memory tasks, achieving remarkably low error rates and accurate pattern recognition capabilities through stable resonance dynamics and unsupervised learning mechanisms.
MATLAB-based license plate location and recognition using color information detection, demonstrating significant effectiveness and high accuracy rates through optimized image processing algorithms.
Implementation of traffic signal light recognition and detection system using computer vision techniques, providing beginners with practical image processing learning direction through feature extraction and classification algorithms.
A PCA-based face recognition system with 40 sets of facial images. Includes random image selection and recognition demonstration with feature extraction and similarity measurement implementations.
Applying Hopfield neural networks to perform association and recognition on noisy digital image patterns "1, 2, 3, 4" to eliminate noise interference, with implementation insights on pattern storage and energy minimization algorithms.
Backpropagation Neural Network for Handwritten Digit Recognition with Support for Digits 0-99