KNN Gesture Recognition Using MATLAB-Inertial Gesture Recognition Based on Mobile Phones

该人脸识别小系统基于Fisher判别原理，采用MATLAB编写，具备友好的GUI接口。

使用离散Hopfield神经网络对模糊数字进行识别，并给出识别结果。可以调节数字的模糊程度，以检验识别效果。

本教程简要介绍了基于梯度下降和delta规则的反向传播算法下多层神经网络的训练及其数值实现。在MATLAB环境中模拟网络，训练它解决字符识别问题和著名的XOR问题。获得的结果非常有趣，表现出优异的性能。由于该算法是函数的近似，它适用于许多需要系统识别和模式分类的问题。关键词：神经网络，多层感知器，训练，模式识别，反向传播，delta规则，梯度下降。

Traffic_sign_recognition: 使用定向梯度直方图（HOG）和基于色域的功能识别交通标志。采用支持向量机（SVM）对图像进行分类，提取交通标志的显著特征，提升识别准确性和可靠性。

This submission includes useful MATLAB functions for speaker recognition using adapted GMM. The implementation details for steps (i)-(iii) can be found in [1]. The fourth function, gmm2sv.m, connects the means (i.e., centers) of the GMM. The cascade means of the adapted GMM are referred to as the GMM supervector (GSV), which is used in the GMM-SVM based speaker recognition system. More information about the GMM-SVM based speaker recognition system can be found in [2]. These codes require the Netlab toolbox. You can access it at: Netlab Toolbox. References: [1] DA Reynolds, TF Quatieri, and RB Dunn, “Speaker Verification Using Adapted Gaussian Mixture Models,” Digital Signal Processing, Vol. 10, pp. 19–41, 2000. [2] Campbell, W. M.; Sturim, D. E.; Reynolds, D. A.; “Support Vector Machines Using GMM Supervectors for Speaker Verification,” Signal Processing Letters.

Code provided by Ruslan Salakhutdinov and Geoff Hinton. Permission is granted for anyone to copy, use, modify, or distribute this program and accompanying programs and documents for any purpose, provided this copyright notice is retained and prominently displayed, along with a note saying that the original programs are available from our web page. The programs and documents are distributed without any warranty, express or implied. As the programs were written for research purposes only, they have not been tested to the degree that would be advisable in any important application. All use of these programs is entirely at the user's own risk. How to make it work:1. Create a separate directory and download all these files into the same directory.2. Download from http://yann.lecun.com/exdb/mnist the following 4 files:- train-images-idx3-ubyte.gz- train-labels-idx1-ubyte.gz- t10k-images-idx3-ubyte.gz- t10k-labels-idx1-ubyte.gz3. Unzip these 4 files by executing:- gunzip train-images-id

这是一个用MATLAB语言编写的车牌识别程序，该程序能够完整识别车牌的字样，并且将每个识别的号码保存在一个Excel表格中，便于后续的查询和管理。 功能概述 图像输入：用户提供带有车牌的图像，程序将自动识别并提取车牌部分。 字符识别：通过图像处理技术，程序可精确识别车牌上的文字和数字。 结果输出：所有识别的车牌号会按顺序保存在Excel文件中，方便数据存储和访问。 使用方法 将车辆图像输入到程序中。 程序自动进行车牌区域定位和字符分割。 最终识别的号码会输出至Excel表格，以便后续数据分析和追踪。 该程序适用于交通管理、停车场管理等多种场景。

Fingerprint Recognition Source Code - MATLAB Version This source code implements fingerprint recognition using MATLAB. The code includes several stages such as image preprocessing, feature extraction, and matching. The provided fingerprint images are used as input for the system. Main Features: Image Preprocessing: Enhances fingerprint image quality for better recognition accuracy. Feature Extraction: Identifies distinctive features of the fingerprint like minutiae points. Matching Algorithm: Compares fingerprints to find similarities. Included in the package are fingerprint images used for testing the algorithm. Image Example: The fingerprint images provided show the original and processed versions of the input data, helping users visualize the recognition process.

《模式识别入门》是一本原版书，内容相当有用，包含相关的MATLAB代码，适合作为美国高校**教材。