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GSNAKE API provides tools for contour modeling, extraction, detection and classification, based on generalized active contour model (g-snake). GSNAKE consists of a set of objects built in C++, suitable for use in the area of feature extraction, chara
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此设计要求能够实现将医学图像进行识别的过程，包括了图像预处理、图像特征提取及分类判决三大模块。在预处理这一步中主要实现的是将彩色图像转换为灰度图像，灰度图像的二值化，直方图修正，去除干扰、噪声以及差异，边缘增强等；第二模块是图像的特征提取。由于对象的物理与几何特性差异，在影像中表现为局部区域的灰度产生明显变化，形成影像特征，而图像特征提取就是对其进行加工、整理、分析、归纳以便提取构成目标影像的特征，得到能反映图像内容区别于其他事物的本质特征；分类判决作为第三模块，则是要在第二步的基础上采用某种分
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第十章
1、 说明对象、类、类结构、消息的基本概念？
答：对象：是客观实体在问题域中的抽象。
类：具有相似或相同性质的对象的抽象就是类。
类结构：类的结构通常有一般----具体（分类结构）整体---抽象（组装结构）
消息：对象之间通信的构造。
2、 面向对象的特征和要素？
答：特征：一致性、多态性、分类性、继承性。要素：共享、封装、抽象。
-a Chapter 10, Note objects, classes, class structure, the basi
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Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clusteri
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本程序实现了对一副图像中的材质不同的物体进行分类,对于材质相同的物体归为一类.-the realization of the image of a different material objects to the classification, For the same material objects classified as a category.
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对象计算，使用图象处理技术对图象上的药品，颗粒等物体进行分类-object computing, the use of image processing technology to image the drugs, such as particle classification of objects
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This paper presents a novel segmentation algorithm for metallographic images, especially those objects without regular boundaries and homogeneous intensity. In metallographic quantification, the complex microstructures make the conventional approache
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This paper presents a novel segmentation algorithm for metallographic images, especially those objects without regular boundaries and homogeneous intensity. In metallographic quantification, the complex microstructures make the conventional approache
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用BP网络对遥感图像进行自动分类，并统计各地物的面积,BP network used for automatic classification of remote sensing images, and objects around the area of statistics
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SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X --> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regula
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图像识别算法。对图像中不同的对象进行分类识别。如三角开，四边形，五边形等。-Image recognition algorithm. The image objects of different classification. Such as the triangle open, quadrilateral, pentagon and so on.
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为了准确地对监控场景中的运动目标进行语义上的分类，提出了一种基于聚类的核主成分分析梯度方向直方图和二又决策树支持向量机的运动目标分类算法。-In order to accurately monitor the movement of scene targets semantic classification, the clustering based on kernel principal component analysis of gradient direction histograms,
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Q. Zhou, J.K. Aggarwal. Tracking and Classifying Moving Objects from Video. 这篇文章另辟蹊径，利用“紧凑度值的变化、运动方向的变化”，区分人、人群、机动车。达到良好的分类效果。是运动目标分类领域的好文章。-Q. Zhou, JK Aggarwal. Tracking and Classifying Moving Objects from Video. This article open a new path, by us
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SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X --> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike reg
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为了准确地对监控场景中的运动目标进行语义上的分类， 提出了一种基于聚类的核主成分分析梯度方向直方图和二叉决策树支持向量机的运动目标分类算法．利用背景减法提取运动目标前景区域， 并识别出潜在候选运动目标．利
用提出的基于聚类的核主成分分析的梯度直方图描述子提取候选运动目标的特征， 以较低维数的数据有效地描述运动目标的有效特征． 将提取的运动目标特征输入二叉决策树支持向量机， 实现多类目标的准确分类． 通过在不同视频序列上的实验验证， 提出的算法对运动目标进行较好地分类， 而且在运算速度方面较传
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此文档包含对卷积神经网络的描述及在图像处理中的应用，对学习卷积神经网络有重要帮助。-The work presented here
uses image classifi cation performance (accurate discrimination between common
classes of objects) as a basis for comparing visual system models, and algorithms
for fi
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This IEEE paper helps for tracking and classification of motion detection.
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通过小波变换对少量样本进行特征提取，达到识别同类物体的效果。-Of a small sample of feature extraction by wavelet transform, to achieve the effect of the recognition of similar objects.
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利用BP神经网络实现三类物体的分类,包含MATLAB和C#两种实现。-Using BP neural network to classify three types of objects.
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All Object Classification file(To classify the objects present in an image)
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