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- W2896761279 abstract "Aimed at the puzzle of the edge discontinuity, over segmentation, slow operation speed, and being difficult to select the best parameters existed in image edge detection algorithm caused by noise sensitivity, in order to get better recognition effect and faster execution speed, the paper presented an algorithm of image geometric feature recognition based on extreme learning machine. In order to facilitate the identification of the geometric features of the image, the algorithm first calculates the optimal threshold by means of algorithm model based on ELM (Extreme Learning Machine), in which, the optimal threshold could farthest separate the foreground and background color, then the threshold is used to limit the path cost function so as to narrow the search scope and improve the speed of algorithm execution. A large number of simulation experiments demonstrated that the presented algorithm could obtain a good effect on image processing. The research results show the rationality and validity of the algorithm based on ELM for image geometric feature recognition." @default.
- W2896761279 created "2018-10-26" @default.
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- W2896761279 date "2018-10-17" @default.
- W2896761279 modified "2023-09-26" @default.
- W2896761279 title "Application Study of Extreme Learning Machine in Image Edge Extraction" @default.
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- W2896761279 doi "https://doi.org/10.1007/978-3-030-01520-6_4" @default.
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