Several Fractal Dimension Calculation Programs for Images
Tested implementations for calculating image fractal dimensions with excellent performance results
Explore MATLAB source code curated for "测试" with clean implementations, documentation, and examples.
Tested implementations for calculating image fractal dimensions with excellent performance results
This program accepts speech input and automatically performs voice recognition. The application can be launched via gui_try.m, which serves as the main entry point for the custom-developed speech recognition system featuring a comprehensive graphical user interface.
This upload contains Vedaldi's MATLAB implementation of D.G. Lowe's SIFT algorithm. Although similar source code exists online, this attached code has been specifically compiled, tested, and verified to run directly without modifications. A critical bug in sift.m has been identified and fixed (with notification sent to Mr. Vedaldi), ensuring reliable feature extraction performance.
A MATLAB-based face recognition program that implements a train-then-test approach, accepting an input image and returning the closest matching face images from the dataset.
Digit recognition system for classifying images of numbers 0 through 9, utilizing a dataset of 100 images with separate training and testing subsets for model validation and performance evaluation
This MATLAB function evaluates the performance of image fusion algorithms by analyzing two original input images and their fused output, generating quantitative metrics to assess fusion quality and effectiveness.
MATLAB programming implementation of the Fruit Fly Optimization Algorithm with function optimization testing, including parameter configuration, objective function definition, and performance evaluation.
Fully functional MATLAB implementation of the SIFT algorithm, personally tested and verified with excellent performance. The code requires minimal modifications for deployment and includes detailed technical documentation.
PCA+Fisher face recognition method tested on ORL face database with promising results, including dimensionality reduction and linear discriminant analysis implementation
I successfully implemented time series signal prediction using wavelet neural network transformation, conducted comprehensive testing with excellent results, and recommend referring to this research which demonstrates effective algorithm implementation through MATLAB/Python code structures.