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真实场景下视频运动目标自动提取方法.主要的研究内容包括运动物体检测,分类和跟踪,研究成果可以广泛地应用在交通管理系统,视频监视系统和军事目标跟踪系统,同时还可以应用在基于内容的视频数据压缩编码中。-Real video scenes under the automatic extraction method of moving targets. The main content includes moving object detection, classification and tracki
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贝叶斯分类器,利用后验概率,对已知属性对象进行分类-Bayesian classifier, the use of posterior probability of the known properties of the object classification
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用C51系列单片机设计物体分级设备的测量光幕-C51 series of single-chip design using object classification screens measuring equipment
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利用物体的几何特征参数,和bp神经网络实现分类。-The use of the geometric characteristics of object parameters, and the realization of bp neural network classification.
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遥感图像的多光谱目标识别,相似度方法实现分类-The multi-spectral remote sensing image object recognition, similarity classification method
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支持向量机,用于图像分类分割,目标检测识别,人工智能信息处理-support vector machine has been widely used in classification and object identification.
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模式识别中,多标签标记中的经典代码,主要用于场景分类,目标识别,结合svm和boost算法对自然场景进行分类,真的很不错,看看吧-Pattern Recognition, multi-tagged in the classic code, mainly used for scene classification, object recognition, combined with svm and boost the natural scene classification algorithm,
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图像分类软件,用MATLAB语言编写,可实现对象的分类和匹配识别-Image classification software used MATLAB language, enabling the object classification and matching recognition
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It is useful to developer who ieterest with detecting object in video surveillance system
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英语文献:基于上下文的目标分类:一个关键性的概述。简单易懂-English literature: Context-based target classification: a critical overview. Straightforward
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K-means算法是最为经典的基于划分的聚类方法,是十大经典数据挖掘算法之一。K-means算法的基本思想是:以空间中k个点为中心进行聚类,对最靠近他们的对象归类。通过迭代的方法,逐次更新各聚类中心的值,直至得到最好的聚类结果。-K-means algorithm is based on the division of the classic clustering method, is ten classic one of data mining algorithm. K-means the
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实现基于OpenCV的SVM目标分类,SVM提取目标跟背景-object classification based on SVM
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视频监控智能分析仿真,目标跟踪、物体分类,需要测试CSHHARP,配置directshow,
-Intelligent analysis and simulation of video surveillance, target tracking, object classification, need to test CSHHARP configuration directshow,
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SVM(support vector machine) 在object classification中的应用. 含java程序和data。-one application of SVM in object classification.
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对数据处理,将对象进行分类,并画出聚类图,设置图中线条颜色,直观地分出对象间的关系-Data processing, object classification, and draw dendrogram, set the graph line color to visually separate the relationship between objects
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图像自相似性计算。基于全局的图像自相似性计算的目标检测-
Global and Efficient Self-Similarity for Object Classification and Detection
From the methods in [1] this code allows to compute self-similarity
hypercubes (SSHs). These SSHs can be obtained from a prototype
as
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基于一篇文章的代码实现-结合场景信息进行的目标分类(文章及文件名)-An article based code implementation- combined with scenes of target classification information (articles and file name)
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All Object Classification file(To classify the objects present in an image)
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该资料中包含了《OpenCV By Example》中文版以及例程程序,该书的目录如下所示:
第1章 OpenCV的探险之旅;
第2章 OpenCV基础知识介绍;
第3章 图形用户界面和基本滤波;
第4章 深入研究直方图和滤波器;
第5章 自动光学检测、目标分割和检测;
第6章 学习目标分类;
第7章 识别人脸部分并覆盖面具;
第8章 视频监控、背景建模和形态学操作;
第9章 学习对象跟踪;
第10章 文本识别中的分割算法;
第11章 使用Tessera
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Constitutional Neural Network Program for Prediction Model as Object Classification
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