文章基本信息

标题：SVM Algorithm for Industrial Defect Detection and Classification
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作者：Krzysztof Lalik ; Mateusz Kozek ; Paweł Gut 等
期刊名称：MATEC Web of Conferences
电子版ISSN：2261-236X
出版年度：2022
卷号：357
页码：1-8
DOI：10.1051/matecconf/202235704004
语种：English
出版社：EDP Sciences
摘要：This article presents a new algorithm for recognizing defects and discontinuities. It is a neural classification algorithm of the SVM class used for the vision system in the technological sequence. At the basis of the used method of Support Vector Machines (SVM) lies the concept of decision-making space, which is divided by building boundaries separating objects with different class affiliation, that is, defects and discontinuities. The Support Vector Machines method is supposed to perform classification tasks by constructing in a multidimensional space hyperplane separating cases belonging to different classes.