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这是细胞识别统计代码程序,值得初学者学习,很实用
值得下-This is the cell identification code statistical procedures, it is worth learning beginners, under very practical worth
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sltoolbox (Statistical Learning Toolbox) organizes a comprehensive set of matlab codes in statistical learning, pattern recognition and computer vision. It includes 256 m-files in 24 categories, which are from low-level computational routines to high
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细胞识别统计系统,采用vc++6.0编写,具有很强的参考价值,适合修改和学习参考。-Cell recognition statistical system, using vc++6.0 to prepare, has a strong reference value for change and learning for reference.
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统计学习工具箱,包括在统计学习,模式识别,计算机视觉方面的matlab程序。-Statistical Learning Toolbox organizes a comprehensive set of matlab codes in statistical learning, pattern recognition and computer vision.
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支持向量机(Support Vector Machines,简称SVM)是在统计学习理论基础上发
展起来的一种新的通用学习方法,它已初步表现出很多优于已有方法的性能。-SVM (Support Vector Machines, referred to as SVM) is based on statistical learning theory developed a new universal learning method, which has been initially show a
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学习统计学及图像处理不可或缺的经典之作,内容丰富,并且有难度!需要好好揣摩学系!-Statistical learning and image processing indispensable classic, rich, and difficult! Department needs a good try to figure out!
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本书从机器学习的角度介绍了基于视觉的运动分析领域的最新算法和系统。-Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visua
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全参考型视频质量评价方法,基于统计和机器学习的方法,发表在2012年TIP-Full reference type video quality assessment method based on statistical and machine learning methods, published in the 2012 TIP
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将基于统计学习理论中的支持向量机(SVM)应用到目标跟踪领域中"该算法不仅能够自动检测和跟踪视场或图像中预先设定好的目标,而且克服了传统目标跟踪系统的缺陷.-Will be based on statistical learning theory, support vector machine (SVM) is applied to the target tracking in "The algorithm can automatically detect and track field of
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行人再识别。人再次鉴定的准确性可以显著提高给定一个训练集,演示了外表的变化与非重叠的两个摄像头。我们测试时是否能保持这种优势直接标注的训练集并非对所有现场camera-pairs可用。给定的训练集捕捉相机A和B之间的对应关系和不同的训练集捕捉相机B和C之间的对应关系,传递鉴定算法(TRID)建议提供了一个分类器(A,C)对外观。该方法是基于统计建模和使用一个边缘化的推理过程。这种方法可以显著减少注释工作固有的学习系统。-Person re-identification accuracy can
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(1)计算图像中每个像素点的LBP模式(等价模式,或者旋转不变+等价模式)。
(2)然后计算每个cell的LBP特征值直方图,然后对该直方图进行归一化处理(每个cell中,对于每个bin,h[i]/=sum,sum就是一副图像中所有等价类的个数)。
(3)最后将得到的每个cell的统计直方图进行连接成为一个特征向量,也就是整幅图的LBP纹理特征向量;
然后便可利用SVM或者其他机器学习算法进行分类识别了。((1) calculate the LBP pattern of each p
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