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Description: Face Dection based on eye locating by SVM in color image
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Size: 648684 |
Author: QiLihua |
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Description: matlab6.5图像处理，基于simulink的图像处理参考书籍-matlab6.5 image processing, based on Simulink image processing reference books
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Size: 8489984 |
Author: ww |
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Description: 支持向量机的工具箱，对于图像处理中的分类识别学习者有着很大帮助。分享快乐！-SVM toolbox for image processing in the classification and identification of learners have a great help to me. To share their happiness!
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Size: 125952 |
Author: hq |
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Description: Face Dection based on eye locating by SVM in color image
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Size: 1939456 |
Author: QiLihua |
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Description: 基于Matlab的指纹识别程序 对指纹图像进行gabbor滤波、二值化、腐蚀等适当处理后 通过SVM等算法 可以识别出新指纹图像是否在原有数据库中。可以用于演示小型的指纹识别系统 -Matlab-based fingerprint identification procedures carried out on the fingerprint image gabbor filtering, binarization, corrosion, etc. After appropriate treatment, such as through the SVM algorithm can identify a new fingerprint image is in the original database. Can be used for demonstration of small-scale fingerprint identification system
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Size: 5292032 |
Author: thusimon |
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Description: 该课件主要陈述了基于内容的图象检索技术的由来，主要的处理技术和未来的发展方向。另外该课件为英文课件，有兴趣的可以下来看下！-The main statement of the courseware content-based image retrieval technology, the origin, the main treatment technologies and the future direction of development. In addition to the courseware courseware in English, interested can facie down!
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Size: 1184768 |
Author: aurora |
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Description: 使用支持向量机对仿人感知器建模，并给出了其在不规则图形面积测量中的应用实例，附有120幅图片及其面积，前100幅用作训练，后20幅用作检验，图片文件默认路径为C:\MATLAB7\work\P100，即应将文件解压到默认路径C:\MATLAB7\work，使用其他路径只需将程序中的图片路径替换即可。-The use of support vector machine perceptron on humanoid modeling, and gives the graphics area in the irregular application of measurement, accompanied by 120 images and its size, 100 for training before and after testing for 20 , the default path for the image file C: MATLAB7workP100, that should extract the files to the default path C: MATLAB7work, the use of other procedures in the path can simply replace the image path can be.
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Size: 135168 |
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Description: SVM matlab GUI可视化界面 直观形象
代码解释比较详细 对GUI学习和svm学习都有帮助-SVM matlab GUI interface intuitive visualization of the image of the code explained in more detail on the GUI SVM learning and learning help
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Size: 496640 |
Author: 刘向阳 |
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Description: 图像检索中一种有效的SVM相关反馈算法.强烈推荐-Image Retrieval in an effective relevance feedback algorithm SVM. Strongly recommended
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Size: 374784 |
Author: sss |
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Description: 主要在对图片加入不同噪声时进行图像复原程序。-Mainly in the picture by adding different noise when the image recovery process.
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Size: 1024 |
Author: 辛江慧 |
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Description: 目的:运用强化学习!多分类器集成!降维方法等最新计算机技术,结合细胞病理知识,设计制作/智能化肺癌细胞病理图像诊断系统0"方法:采集细胞图像,运用基于强化学习的图像分割法将细胞区域从背景中分离出来 运用基于样条和改进2方法对重叠细胞进行分离和重构 提取40个细胞特征用于贝叶斯!支持向量机!紧邻和决策树4种分类器,集成产生肺癌细胞分类结果 建立肺癌细胞病理图库,运用基于等降维方法对细胞进行比对,给予未定型癌细胞分类"结果:/智能化肺癌细胞病理诊断系统0应用于临床随机1200例肺部病灶穿刺细胞学涂片,肺癌识别诊断率94180 ,假阳性率1185 ,假阴性率3135 ,肺癌分类识别率82190 ,核异型细胞识别率74120 "结论:/智能化肺癌早期细胞病理诊断系统0对肺癌细胞涂片诊断率高,克服了肺癌细胞病理诊断过程中取检细胞数量少,重叠细胞识别率低,涂片背景及染色差异等干扰因素,可辅助临床肺部病灶的穿刺细胞病理诊断"-Objective Design and develop a intelligent cytopathological lung cancer diagnosing system(ICLCDS) utilizing the latest computer technologies(including Reinforcement Lcaming Multiple Classifier Fusion and Dimcnsionality Reduction) and the cy-topathological knowledge on lung canccrcclls Methods We got information ofcclls and segregated cell regions in a slice image using an magi scgmcntouon a址orithm Sascd on reinforcement lcaming including rcconstmction of overlapped cell area Sascd on B一Spline and improved dcBoor-Cox Mcthoc} We comSincd multiple classifiers including Baycsian classific:Support Vector Machine(SVM)
classific K-Ncarcst NcighSour( KNN) and Decision c classific to achieve an accurate result of cytopathological lung cancer diag-nosis Results Experimental results on 1 200 cases randomly selected we as follows the accurate diagnosis rate for lung cancer idcn-tification was the false positive rate was 1. 8`J /c‘the false negative rate was 3. 3`J /c‘the type class
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Size: 221184 |
Author: 高阳 |
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Description: 基于支持向量机的相关反馈图像检索算法
相关反馈技术是近年来在图像检索中较为重要的
研究方法, 从机器学习的角度, 以支持向量机(SVM ) 为分类器, 提出了一种新的相关反馈方法-Support vector mach ine based relevance
feedback algorithm in image retrieval
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Size: 191488 |
Author: 张三风 |
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Description: 23825781svmSVM matlab GUI可视化界面 直观形象 代码解释比较详细 对GUI学习和svm学习都有帮助-23825781svmSVM matlab GUI interface intuitive visual image of the code to explain in more detail on the GUI has to help learning and svm learning
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Size: 200704 |
Author: myzone |
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Description: SVM 在JAVA中的运用，简单的DEMO测试，用于做图像识别分析。支援向量机源码调用实例里面有测试资料供简单测试。-The use of SVM in JAVA, simple DEMO test, used to make image recognition analysis. Support vector machine called an instance of source test data for which there is a simple test.
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Size: 134144 |
Author: lion |
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Description: 利用级联SVM的人体检测方法从图像中检测出人体是计算机视觉应用中的关键步骤。通过一个由简到繁的级联线性SVM分类器将级
联拒绝的机制与梯度方向直方图特征相结合,实现了一个准确和快速的人体检测器,整个检测器由级联的线性
SVM分类器组成。实验结果表明,在保持Dalal算法检测准确性的同时,大幅的提高了检测速度,每秒平均可以处
理12帧左右的320 ×240的图像。-Human detection using cascade SVM method detected from the images of computer vision applications, the human body is a key step. From the simple to the complex through a cascade of linear SVM classifier with the cascade mechanism of rejection combined histograms of oriented gradients to achieve an accurate and rapid detection of the human body, the detector by a cascade of linear SVM classifier component. The results show that the accuracy in maintaining Dalal algorithm to detect the same time, substantially increase the detection rate of 12 frames per second on average can process about 320 × 240 image.
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Size: 482304 |
Author: lilin |
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Description: 支持向量机的matlab实现，各位可以试试一试。在图像处理和人脸识别上效果还可以-Matlab support vector machine implementation, you can try try. In image processing and recognition of the effect can also be
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Size: 1190912 |
Author: YOUYOU |
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Description: its the matlab coding for pattern recoganization in image processing using genetic algorithm-its the matlab coding for pattern recoganization in image processing using genetic algorithm
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Size: 224256 |
Author: suresh |
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Description: 实现了 SVM 在医学图像分类中的应用，通过医学图像的实验结果验证了该方法的有效性。
对 SVM 算法进行了深入研究，结合量子行为的粒子群算法的优点，提出了一种量子行为的粒子群算法和 SVM 结合的混合分类模型，应用于医学图像的分类中。
深入研究了 K-means 算法，结合了无监督聚类和监督分类方法的优点，提出了一种 K-means 和 SVM 结合的混合分类模型，并应用于医学图像的分类中。
利用粒子群和量子行为的粒子群算法对 K-means 算法进行了改进，并将改进的K-means 算法与 SVM 算法结合形成全自动分类模型，并且把它应用于医学图像的分类中。
-SVM in the classification of medical image applications, medical images through the experimental results verify the effectiveness of the method. SVM algorithm conducted in-depth research, combined with the quantum behavior of the advantages of particle swarm optimization, PSO and SVM combined behavior of a quantum mixed classification model, applied to medical image classification. In-depth study of the K-means algorithm combines the advantages of unsupervised clustering and supervised classification method, propose a hybrid combination of a K-means and SVM classification model, and applied to the classification of medical images. Improved particle swarm algorithm using particle swarm and quantum behavior of the K-means algorithm, and improved K-means algorithm and SVM algorithm combined with the formation of a fully automatic classification model, and apply it to medical image classification.
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Size: 1626112 |
Author: 招伟杰 |
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Description: Cervical cancer is one of the deadliest cancers known and is also a key research area in image processing. The main problem with this cancer is that it cannot be detected as it doesn’t throw any symptoms until the final stages. This is attributed to the cancer itself and also to the lack of pathologists available to screen the cancer. Here we have proposed a novel approach to classify the various malignancies in cervical cyto images using the textural properties of the cervical cyto image. For grouping the stages of the cancer we have employed a decision based support system that would help classify the stages of the cancer and help the pathologist detect the cancer better. The proposed image has been tested with a set of images and has proved to be efficient.
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Size: 171008 |
Author: michael |
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Description: 该文献主要介绍了基于训练样本自动选取的SVM彩色图像分割方法，详细的对比了各种方法的优缺点(This paper mainly introduces the SVM color image segmentation method based on the training sample automatically, and compares the advantages and disadvantages of various methods in detail)
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Size: 6543360 |
Author: 飘逸的猪 |
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