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Avtomatika i Telemekhanika, 2016, Issue 3, Pages 99–108 (Mi at14404)  

This article is cited in 3 scientific papers (total in 3 papers)

System Analysis and Operations Research

The maximal likelihood enumeration method for the problem of classifying piecewise regular objects

A. V. Savchenko

National Research University Higher School of Economics, Laboratory of Algorithms and Technologies for Network Analysis, Nizhny Novgorod, Russia
Full-text PDF (155 kB) Citations (3)
References:
Abstract: We study the recognition problem for composite objects based on a probabilistic model of a piecewise regular object with thousands of alternative classes. Using the model's asymptotic properties, we develop a new maximal likelihood enumeration method which is optimal (in the sense of choosing the most likely reference for testing on every step) in the class of “greedy” algorithms of approximate nearest neighbor search. We show experimental results for the face recognition problem on the FERET dataset. We demonstrate that the proposed approach lets us reduce decision making time by several times not only compared to exhaustive search but also compared to known approximate nearest neighbors techniques.
Funding agency Grant number
National Research University Higher School of Economics 15-01-0019
Presented by the member of Editorial Board: B. T. Polyak

Received: 04.02.2015
English version:
Automation and Remote Control, 2016, Volume 77, Issue 3, Pages 443–450
DOI: https://doi.org/10.1134/S0005117916030061
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: A. V. Savchenko, “The maximal likelihood enumeration method for the problem of classifying piecewise regular objects”, Avtomat. i Telemekh., 2016, no. 3, 99–108; Autom. Remote Control, 77:3 (2016), 443–450
Citation in format AMSBIB
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Linking options:
  • https://www.mathnet.ru/eng/at14404
  • https://www.mathnet.ru/eng/at/y2016/i3/p99
  • This publication is cited in the following 3 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Avtomatika i Telemekhanika
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    Abstract page:193
    Full-text PDF :63
    References:58
    First page:39
     
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