Automatic binary data classi¯cation using a modi¯ed allen-cahn equation

Sangkwon Kim, Junseok Kim

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we propose an automatic binary data classi¯cation method using a modi¯ed Allen-Cahn (AC) equation. The modi¯ed AC equation was originally developed for image segmentation. The equation consists of the AC equation with a ¯delity term which enforces the solution to be the given data. In the proposed method, we start from a coarse grid and re¯ne the grid until the accuracy of the data classi¯cation reaches a given tolerance. Therefore, we can avoid a laborious trial and error procedure. For a numerical method for the modi¯ed AC equation, we use a recently developed explicit hybrid scheme. We perform several 2D and 3D computational tests to demonstrate the performance of the proposed method. The computational results con¯rm that the proposed algorithm is automatic.

Original languageEnglish
Article number2150013
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
DOIs
Publication statusAccepted/In press - 2020

Keywords

  • Binary data classi¯cation
  • Modi¯ed Allen-Cahn equation
  • Operator splitting method

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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