Classification by discrete optimization

Shmuel Peleg*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

An approach to classification is described where an evaluation function is available. Deterministic classifications are evaluated by a heuristic function, and a special search procedure is applied to find a classification optimizing this function. A specific application to image segmentation is presented, including several examples. The major difference between this approach and previous optimization attempts is the use of deterministic ratter than probabilistic classifications.

Original languageEnglish
Pages (from-to)122-130
Number of pages9
JournalComputer Vision, Graphics, and Image Processing
Volume25
Issue number1
DOIs
StatePublished - Jan 1984

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