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Description: 基于GMM的概率神经网络PNN具有良好的泛化能力，快速的学习能力，易于在线更新,并具有统计学的贝叶斯估计理论基础，已成为一种解决像说话人识别、文字识别、医疗图像识别、卫星云图识别等许多实际困难分类问题的很有效的工具。而且PNN不但具有GMM的大部分优点，还具有许多GMM没有的优点，如强鲁棒性，需要更少的训练语料，可以和其他网络其他理论无缝整合等。-GMM based probabilistic neural network PNN good generalization ability, the ability to learn fast, easy online updates, and with the Bayesian statistical theory based on estimates, and has become a solution as speaker recognition, text recognition, medical image recognition, satellite images and other real recognition when difficulties classification of very effective tool. But GMM PNN is not only the most advantages, but also has many advantages GMM not as strong robustness, require less training corpus, and other networks to other theories, such as seamless integration.
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Size: 7168 |
Author: 姜正茂 |
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Description: 基于VC++编程界面的图像纹理处理的源程序，供大家参考！-VC programming interface based on the image texture of the source, for your reference!
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Size: 439296 |
Author: 董树晶 |
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Description: 对图像进行GMM（混合高斯）拟合后用EM算法进行分割-Image GMM (Gaussian Mixture) after fitting algorithm using EM Segmentation
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Size: 1024 |
Author: mona |
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Description: gmm和bayes估计，适合于图像处理中图像分割。-gmm and Bayes estimates, suitable for image processing in image segmentation.
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Size: 121856 |
Author: 汪世刚 |
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Description: 台湾张智星关于GMM的文档，很详细，做图像识别或说话人识别的对GMM有兴趣的话可以看一下-Zhang Zhi Star Taiwan GMM about the documents, in great detail, to do image recognition or speaker recognition of GMM are interested can look at
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Size: 195584 |
Author: 董飞 |
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Description: 高斯混合模型是單一高斯機率密度函數的延伸，由於GMM 能夠平滑地近似任意形狀的密度分佈，因此近年來常被用在語音與語者辨識，得到不錯的效果。-Gaussian mixture model is a single Gaussian probability density function of the extension, as the GMM can approximate arbitrary smooth shape of the density distribution, it is often used in recent years in speech and speaker recognition, get good results.
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Size: 195584 |
Author: geyu |
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Description: A common method for real-time segmentation of
moving regions in image sequences involves “background
subtraction,” or thresholding the error between
an estimate of the image without moving objects and
the current image. The numerous approaches to this
problem differ in the type of background model used
and the procedure used to update the model. This paper
discusses modeling each pixel as a mixture of Gaussians
and using an on-line approximation to update
the model. The Gaussian distributions of the adaptive
mixture model are then evaluated to determine which
are most likelyt o result from a background process.
Each pixel is classified based on whether the Gaussian
distribution which represents it most effectivelyis considered
part of the background model.
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Size: 186368 |
Author: ajinkya |
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Description: MATLAB中实现GMM算法的原始代码，实现图像分割-GMM algorithm implemented in MATLAB source code for image segmentation
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Size: 12288 |
Author: 许浩然 |
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Description: GMM模型和贝叶斯分类器 用于视频图像的处理-GMM model and the Bayesian classifier for video image processing
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Size: 1024 |
Author: isee |
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Description: C++和opencv相结合的关于图像中高斯建模的程序。-C++ and opencv combination of Gaussian model on the image of the procedure.
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Size: 2808832 |
Author: hehe |
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Description: background subtraction using g-background subtraction using gmm
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Size: 3072 |
Author: jagan |
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Description: 利用OPENCV來實現高斯混合模型的背景相減，可看到當前影像、前景及背景-OPENCV to achieve using GMM background subtraction, we can see the current image, foreground and background
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Size: 1024 |
Author: justin |
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Description: 本代码建立高斯混合模型(高斯多模型)(GMM)，将其用于计算机视觉领域的视频目标检测/视频监控/运动检测/运动目标检测/视频目标跟踪等相关应用中。-This code sets up Gaussian mixture model(Gaussion Mixture Model, GMM) with image sequences for the research and application field of computer vision, using GMM for visual object detection(video object detection), visual surveillance, motion detection, motion tracking, visual object tracking, video object tracking, etc.
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Size: 16384 |
Author: 朱亮亮 |
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Description: PCA、NMF、LDA、GMM这些算法的matlab实现
解压后文件夹中包含需识别的库、课题要求、课题报告和实现的代码。-PCA,NMF,LDA,GMA these four algorithms Matlab code are referred here.
After being decompressed,the file shows the image library to be dealt with,the requirement of the project,the report of the project and the code.
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Size: 9821184 |
Author: davidson |
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Description: 混合高斯背景建模用于检出背景，并提取前景，在OPENCV环境下操作进行的。是数字图像处理领域不可缺少的一种处理方式。OPENCV库里含有的函数在数字图像中的作用都是不可获取的，用起来简单又便捷，建议OPENCV从头认真学起-Gaussian mixture background modeling for the detection of background and foreground extraction, OPENCV environment in the operation. The field of digital image processing an indispensable approach. OPENCV library containing the function s role in the digital images are not obtained, it is simple and easy to use, it is recommended to learn the OPENCV seriously from the beginning.
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Size: 1024 |
Author: yuanyuan |
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Description: 基于GMM的概率神经网络PNN具有良好的泛化能力，快速的学习能力，易于在线更新,并具有统计学的贝叶斯估计理论基础，已成为一种解决像说话人识别、文字识别、医疗图像识别、卫星云图识别等许多实际困难分类问题的很有效的工具。而且PNN不但具有GMM的大部分优点，还具有许多GMM没有的优点，如强鲁棒性，需要更
-image processing
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Size: 35840 |
Author: hbing |
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Description: 介绍Opencv这个图像处理库环境下的GMM建模与EM算法，从数学的角度深入分析高斯建模和EM算法-Introduce the the Opencv this image processing GMM modeling the EM algorithm in the library environment, in-depth analysis from a mathematical point of the Gaussian model and the EM algorithm
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Size: 451584 |
Author: xue |
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Description: 混合高斯背景建模C++源程序
在进行前景检测前，先对背景进行训练，对图像中每个背景采用一个混合高斯模型进行模拟，每个背景的混合高斯的个数可以自适应。-Before the the mixed Gaussian background the modeling C++ source. During foreground detection, background training, each background image using a Gaussian mixture model simulation, adaptive Gaussian mixture number of each background.
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Size: 7168 |
Author: sjtu-lsz |
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Description: 混合高斯模型在运动检测中的应用，检测视频中的运动物体，做出其背景图像和前景图像-Gaussian mixture model in motion detection to detect moving objects in the video to make the background image and the foreground image
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Size: 1024 |
Author: 张茂华 |
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Description: My implementation of Stauffer & Grimson's GMM(Background subtraction
Drawbacks of Stauffer & Grimson's GMM
Since its pixel based model fitting,
a) lots of unwanted small blobs are scattered all over the frame. e.g. UCSD demo
b) main blobs aren't completely foreground. e.g. CVC, Barcelona Univ demo)
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Size: 26624 |
Author: hamed tirandaz
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