Gated Boltzmann machine in texture modeling

Tele Hao*, Tapani Raiko, Alexander Ilin, Juha Karhunen

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    5 Citations (Scopus)


    In this paper, we consider the problem of modeling complex texture information using undirected probabilistic graphical models. Texture is a special type of data that one can better understand by considering its local structure. For that purpose, we propose a convolutional variant of the Gaussian gated Boltzmann machine (GGBM) [12], inspired by the co-occurrence matrix in traditional texture analysis. We also link the proposed model to a much simpler Gaussian restricted Boltzmann machine where convolutional features are computed as a preprocessing step. The usefulness of the model is illustrated in texture classification and reconstruction experiments.

    Original languageEnglish
    Title of host publicationArtificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings
    Number of pages8
    Volume7553 LNCS
    EditionPART 2
    Publication statusPublished - 2012
    MoE publication typeA4 Article in a conference publication
    EventInternational Conference on Artificial Neural Networks - Lausanne, Switzerland
    Duration: 11 Sept 201214 Sept 2012
    Conference number: 22

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 2
    Volume7553 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    ConferenceInternational Conference on Artificial Neural Networks
    Abbreviated titleICANN


    • Deep Learning
    • Gated Boltzmann Machine
    • Gaussian Restricted Boltzmann Machine
    • Texture Analysis


    Dive into the research topics of 'Gated Boltzmann machine in texture modeling'. Together they form a unique fingerprint.

    Cite this