Search - neural network face recognition using matlab

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[AI-NN-PR] NeuroFaceDemo DL : 0: Face Recognition Demo using Neural Networks-Face Recognition Demo using Neural Network ks
Update : 2025-02-17 Size : 3.29mb Publisher : 李琳莉
[AI-NN-PR] neuralnetwork_face_recognize DL : 0: 用人工神经网络进行人脸识别-using artificial neural networks face recognition
Update : 2025-02-17 Size : 1.71mb Publisher : xz
[File Format] FACERECOGNITIONBASEDONFRACTALANDGENETICALGORITHMS. DL : 0: 本文的题目是基于分形和遗传算法的人脸识别方法，对有限人群提出一种采用分形特征和遗传聚类的识别方法: 将图像分成很多小区域, 分别计算各个区域的分形特征, 以充分利用图像二维信息同一个模式有多个样本, 通过遗传算法进行聚类以得到最优解实现不变性识别. 最后采用ORL 人脸图像库的一组图像对比了新方法、本征脸法和自联想神经网络方法, 结果表明该方法的识别率, 与本征脸法相似, 比自联想神经网络高.-The title of this article is based on fractal and genetic algorithms for face recognition method, a crowd of limited use of fractal characteristics and the identification of genetic clustering methods: the image is divided into many small regions, each region were calculated fractal characteristics, to take full advantage of two-dimensional image information with a model for a number of samples, through the genetic clustering algorithm in order to obtain the optimal solution to achieve invariant recognition. Finally, using ORL face image database of a group of image contrast of the new methods, eigenface law and auto-associative neural network methods, results show that the method of recognition rate, with the eigenface method is similar to auto-associative neural network than high.
Update : 2025-02-17 Size : 372kb Publisher : 阳关
[AI-NN-PR] FaceRecognition DL : 0: 一个用神经网络方法实现人脸识别的程序，来源于CMU的machine learning 课程作业，具有参考价值-A method using neural network face recognition procedures derived from the machine learning courses CMU operations, reference value
Update : 2025-02-17 Size : 582kb Publisher : 小威
[Graph Recognize] dctannprotected DL : 0: High information redundancy and correlation in face images result in efficiencies when such images are used directly for recognition. In this paper, discrete cosine transforms are used to reduce image information redundancy because only a subset of the transform coefficients are necessary to preserve the most important facial features such as hair outline, eyes and mouth. We demonstrate experimentally that when DCT coefficients are fed into a backpropagation neural network for classification, a high recognition rate can be achieved by using a very small proportion of transform coefficients. This makes DCT-based face recognition much faster than other approaches.-High information redundancy and correlation in face images result in inefficiencies when such images are used directly for recognition. In this paper, discrete cosine transforms are used to reduce image information redundancy because only a subset of the transform coefficients are necessary to preserve the most important facial features such as hair outline, eyes and mouth. We demonstrate experimentally that when DCT coefficients are fed into a backpropagation neural network for classification, a high recognition rate can be achieved by using a very small proportion of transform coefficients. This makes DCT-based face recognition much faster than other approaches.
Update : 2025-02-17 Size : 25kb Publisher : mhm
[2D Graphic] face_recognition_PCAPBPNN DL : 0: The purpose of this work is to identify a given face image using main features of face. The dimensionality of face image is reduced by the Principal component analysis (PCA, using eigenfaces method) and the recognition is done by the Back propagation Neural Network (BPNN).
Update : 2025-02-17 Size : 2.97mb Publisher : amine
[AI-NN-PR] pca-som DL : 0: matlab下采用som神经网络算法进行100个人脸识别，可扩展性强。-som neural network using matlab under 100 face recognition algorithm, scalability.
Update : 2025-02-17 Size : 3.36mb Publisher : 王超
[AI-NN-PR] Face-orientation-recognition DL : 0: 本课题研究的步骤如下：先提取人脸的特征向量；产生训练样本和测试样本；再用LVQ创建神经网络模型，该模型用训练样本进行训练调整权值；用测试样本对建立的人脸朝向识别模型进行验证，要求有较高的识别率。本课题要求使用LVQ神经网络的算法进行Matlab仿真，对人脸朝向进行有效的判断和识别。 -This study is the following steps: first extract facial feature vector generate training and testing samples reuse create LVQ neural network model, which is trained using training samples to adjust the weights using the test sample towards the establishment of a human face recognition model validated requires a higher recognition rate. This topic requires the use of LVQ neural network algorithm Matlab simulation, the human face towards effective judgment and identification.
Update : 2025-02-17 Size : 129kb Publisher : 吴军
[AI-NN-PR] CNN DL : 0: This project provides matlab class for implementation of convolutional neural networks. This networks was developed by Yann LeCun and have sucessfully used in many practical applications, such as handwritten digits recognition, face detection, robot navigation and others (see references for more info). Because of some architectural features of convolutional networks, such as weight sharing it is imposible to implement it using Matlab Neural Network Toolbox without it s source modifications.
Update : 2025-02-17 Size : 613kb Publisher : 郭志
[Special Effects] bp-netual-net DL : 0: 多层前向反馈式神经网络是目前应用比较广泛的人工神经网络，其中BP(Back Propagation network，简称BP网络)学习算法是最著名的多层前向反馈式神经网络训练算法之一。该算法在图像处理和图像识别领域已经取得令人瞩目的成就，其主要思想是利用已知确定结果的样本模式对网络进行训练，然后利用训练好的网络进行图像的处理或识别。本文将讨论用MATLAB实现BP神经网络对人脸角度的分析。-Multilayer feedforward neural network feedback is used widely in artificial neural networks, which BP (Back Propagation network, referred to as the BP network) learning algorithm is one of the feedback neural network training algorithm of the most famous multi-front. The algorithm in the field of image processing and image recognition has made remarkable achievements, the main idea is to use the known samples to determine the results of network training mode, and then use the trained network for image processing or recognition. This article will discuss the human face angle analysis using MATLAB BP neural network.
Update : 2025-02-17 Size : 2kb Publisher : 张鹏
[Software Engineering] nbpfcrudgen-0.35.2-8.1_patch1-impl DL : 0: Face recognition using BPNN. Contains 1.Face recognition using Back propagation neural network (customize code) code using matlab. 2. Face recognition using Back propagation network (builtin) code using matlab.Project closed for now,Adeel Raza Azeemi
Update : 2025-02-17 Size : 88kb Publisher : suresh
[AI-NN-PR] renlainshibie DL : 0: 基于BP神经网络的人脸识别,用matlab实现的-Based on BP neural network face recognition, using matlab to achieve
Update : 2025-02-17 Size : 7.64mb Publisher : 蓝枫
[Other] CroppedYale DL : 0: 通过神经网络利用matlab和python实现人脸识别(Face recognition using MATLAB and python through neural network)
Update : 2025-02-17 Size : 55.78mb Publisher : SpongeB0B
[Special Effects] 神经网络实现人脸识别任务 DL : 0: 通过python第三方库和matlab神经网络工具箱实现人脸识别(Face recognition using MATLAB and python through neural network)
Update : 2025-02-17 Size : 55.71mb Publisher : SpongeB0B