Description: 用MATLAB编写的svm源程序，可以实现支持向量机，用于特征分类或提取-SVM prepared using MATLAB source code, you can achieve the support vector machine for feature classification or extraction Platform: |
Size: 153600 |
Author:linna |
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Description: 采用matlab，实现了gabor滤波的核心功能-gabor filter is very famous and really useful for texture feature extraction and image retrivel. attached code is wrriten well using matlab. More detail can be referenced in the paper <texture features for browsing and retrieval of image data> Platform: |
Size: 1209344 |
Author:rocky |
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Description: 用MATLAB编写的svm源程序，可以实现支持向量机，用于特征分类或提取-MATLAB source code written using svm, support vector machine can be achieved for feature classification or extraction Platform: |
Size: 198656 |
Author:王世涛 |
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Description: 使用Gabor小波对图像进行特征提取，代码可以直接使用-Using the Gabor wavelet feature extraction, the code can be used directly Platform: |
Size: 100352 |
Author:qq445988770 |
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Description: 这是一个使用了Gabor特征提取和人工智能的人脸检测系统源代码
使用步骤：
1. 拷贝所有文件到MATLAB工作目录下(确认已经安装了图像处理工具箱和人工智能工具箱)
2. 找到"main.m"文件
3. 命令行中运行它
4. 点击"Train Network"，等待程序训练好样本
5. 点击"Test on Photos"，选择一个.jpg图片，识别。
6. 等待程序检测出人脸区域
createffnn.m, drawrec.m, gabor.m, im2vec.m, imscan.m, loadimages.m, main.m, template1.png, template2.png, trainnet.m-This is a use of the Gabor feature extraction and artificial intelligence source code of face detection system using the steps: 1. Copy all files to the MATLAB working directory (sure you have installed the Image Processing Toolbox, and artificial intelligence toolbox) 2. Found " main.m " file 3. the command line, run it 4. Click the" Train Network " , waiting for a good sample of the training program 5. Click the" Test on Photos " , select a. jpg image recognition. 6. Wait for the program detects the face region createffnn.m, drawrec.m, gabor.m, im2vec.m, imscan.m, loadimages.m, main.m, template1.png, template2.png, trainnet.m Platform: |
Size: 140288 |
Author:郑碧波 |
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Description: unconstrained face images has ... time required for feature extraction using a 64-by-64 image is 0.0176 seconds. ... Index Terms: Matlab, source, code, LBP, Platform: |
Size: 18432 |
Author:basma_ammour |
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Description: unconstrained face images has ... time required for feature extraction using a 64-by-64 image is 0.0176 seconds. ... Index Terms: Matlab, source, code, LBP, Platform: |
Size: 123904 |
Author:basma_ammour |
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Description: unconstrained face images has ... time required for feature extraction using a 64-by-64 image is 0.0176 seconds. ... Index Terms: Matlab, source, code, LBP, Platform: |
Size: 17408 |
Author:basma_ammour |
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Description: unconstrained face images has ... time required for feature extraction using a 64-by-64 image is 0.0176 seconds. ... Index Terms: Matlab, source, code, LBP, Platform: |
Size: 10240 |
Author:basma_ammour |
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Description: unconstrained face images has ... time required for feature extraction using a 64-by-64 image is 0.0176 seconds. ... Index Terms: Matlab, source, code, LBP, Platform: |
Size: 13312 |
Author:basma_ammour |
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Description: 图像处理 并行处理 matlab Since images can be represented by 2D or 3D matrices and the MATLAB processing engine
relies on matrix representation of all entities, MATLAB is particularly suitable for implemen‐
tation and testing of image processing workflows. The Image Processing Toolbox
™
(IPT)
includes all the necessary tools for general-purpose image processing incorporating more than
300 functions which have been optimised to offer good accuracy and high speed of processing.
Moreover, the built-in Parallel Computing Toolbox
™
(PCT) has recently been expanded and
now supports graphics processing unit (GPU) acceleration for some functions of the IPT.
However, for many image processing applications we still need to write our own code, either
in MATLAB or, in the case of GPU-accelerated applications requiring specific control over
GPU resources, in CUDA (Nvidia Corporation, Santa Clara, CA, USA).-the first part is dedicated to some essential tools of the IPT that can be used in
image analysis and assessment as well as in extraction of useful information for further
processing and assessment. These include retrieving information about digital images, image
adjustment and processing as well as feature extraction and video handling. The second part
is dedicated to GPU acceleration of image processing techniques either by using the built-in
PCT functions or through writing our own functions. Each section is accompanied by MAT‐
LAB example code. Platform: |
Size: 629760 |
Author:阿新 |
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Description: 利用MATLAB对脸部特征进行降维提取，数据齐全，可以直接运行。-Using MATLAB to reduce the dimension of facial features extraction, data is complete, can be run directly. Platform: |
Size: 6667264 |
Author:马振磊 |
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Description: comparision of two rgb images using edge detectors which will be useful for feature extraction and object presence in the image Platform: |
Size: 9216 |
Author:AShalatha |
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Description: 利用matlab提取声音的基本特征，包络、MFCC、声谱图、能量。代码不复杂，但是省去大家找这些的时间。-The basic feature extraction using matlab sound envelope, MFCC, sonograms, energy. Code is not complicated, but we look for these omitted time. Platform: |
Size: 9378816 |
Author:月光下的魔术师V |
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Search - feature extraction using matlab code