Gated Boltzmann machine in texture modeling

Tele Hao; Tapani Raiko; Alexander Ilin; Juha Karhunen

doi:10.1007/978-3-642-33266-1_16

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 proceeding › Conference contribution › Scientific › peer-review

5 Citations (Scopus)

Abstract

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 language	English
Title of host publication	Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings
Pages	124-131
Number of pages	8
Volume	7553 LNCS
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-33266-1_16
Publication status	Published - 2012
MoE publication type	A4 Article in a conference publication
Event	International Conference on Artificial Neural Networks - Lausanne, Switzerland Duration: 11 Sept 2012 → 14 Sept 2012 Conference number: 22

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	7553 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Artificial Neural Networks
Abbreviated title	ICANN
Country/Territory	Switzerland
City	Lausanne
Period	11/09/2012 → 14/09/2012

Keywords

Deep Learning
Gated Boltzmann Machine
Gaussian Restricted Boltzmann Machine
Texture Analysis

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10.1007/978-3-642-33266-1_16

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Hao, T., Raiko, T., Ilin, A., & Karhunen, J. (2012). Gated Boltzmann machine in texture modeling. In Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings (PART 2 ed., Vol. 7553 LNCS, pp. 124-131). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7553 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-33266-1_16

Hao, Tele ; Raiko, Tapani ; Ilin, Alexander et al. / Gated Boltzmann machine in texture modeling. Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings. Vol. 7553 LNCS PART 2. ed. 2012. pp. 124-131 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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author = "Tele Hao and Tapani Raiko and Alexander Ilin and Juha Karhunen",

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Hao, T, Raiko, T, Ilin, A & Karhunen, J 2012, Gated Boltzmann machine in texture modeling. in Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings. PART 2 edn, vol. 7553 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 7553 LNCS, pp. 124-131, International Conference on Artificial Neural Networks, Lausanne, Switzerland, 11/09/2012. https://doi.org/10.1007/978-3-642-33266-1_16

Gated Boltzmann machine in texture modeling. / Hao, Tele; Raiko, Tapani; Ilin, Alexander et al.
Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings. Vol. 7553 LNCS PART 2. ed. 2012. p. 124-131 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7553 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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AB - 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.

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Hao T, Raiko T, Ilin A, Karhunen J. Gated Boltzmann machine in texture modeling. In Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings. PART 2 ed. Vol. 7553 LNCS. 2012. p. 124-131. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-33266-1_16

Gated Boltzmann machine in texture modeling

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Keywords

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