多维模式变化检测的新方法——第二部分

IF 3.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Artificial Intelligence and Soft Computing Research Pub Date : 2021-05-29 DOI:10.2478/jaiscr-2021-0013
T. Gałkowski, A. Krzyżak, Zofia Patora-Wysocka, Z. Filutowicz, Lipo Wang
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引用次数: 1

摘要

摘要本文提出了一种基于Parzen核估计的边缘曲线三维形状突变检测算法。这些问题通常出现在计算机视觉的各个领域,例如边缘检测、生物信息学和卫星图像处理。在许多工程问题中,突变检测有助于故障保护,例如在描述机械系统中物体的静态和动态特性的函数中进行跳变检测。我们开发了一种算法来检测非参数性质的突变,并利用多元函数及其导数的Parzen回归估计。在测试中,我们特别但不完全地将这种方法应用于两个变量的函数。
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A New Approach to Detection of Changes in Multidimensional Patterns - Part II
Abstract In the paper we develop an algorithm based on the Parzen kernel estimate for detection of sudden changes in 3-dimensional shapes which happen along the edge curves. Such problems commonly arise in various areas of computer vision, e.g., in edge detection, bioinformatics and processing of satellite imagery. In many engineering problems abrupt change detection may help in fault protection e.g. the jump detection in functions describing the static and dynamic properties of the objects in mechanical systems. We developed an algorithm for detecting abrupt changes which is nonparametric in nature and utilizes Parzen regression estimates of multivariate functions and their derivatives. In tests we apply this method, particularly but not exclusively, to the functions of two variables.
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来源期刊
Journal of Artificial Intelligence and Soft Computing Research
Journal of Artificial Intelligence and Soft Computing Research COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
7.00
自引率
25.00%
发文量
10
审稿时长
24 weeks
期刊介绍: Journal of Artificial Intelligence and Soft Computing Research (available also at Sciendo (De Gruyter)) is a dynamically developing international journal focused on the latest scientific results and methods constituting traditional artificial intelligence methods and soft computing techniques. Our goal is to bring together scientists representing both approaches and various research communities.
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