Model-based learning for point pattern data

Ba-Ngu Vo, Nhan Dam, Dinh Phung, Quang N. Tran, Ba-Tuong Vo

Research output: Contribution to journalArticleResearchpeer-review

12 Citations (Scopus)


This article proposes a framework for model-based point pattern learning using point process theory. Likelihood functions for point pattern data derived from point process theory enable principled yet conceptually transparent extensions of learning tasks, such as classification, novelty detection and clustering, to point pattern data. Furthermore, tractable point pattern models as well as solutions for learning and decision making from point pattern data are developed.

Original languageEnglish
Pages (from-to)136-151
Number of pages16
JournalPattern Recognition
Publication statusPublished - Dec 2018


  • Classification
  • Clustering
  • Multiple instance learning
  • Novelty detection
  • Point pattern
  • Point process
  • Random finite set

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