DeepArtist: A Dual-Stream Network for Painter Classification of Highly-Varying Image Resolutions

Doron Nevo; Eli O. David; Nathan S. Netanyahu

doi:10.1007/978-3-031-15937-4_49

DeepArtist: A Dual-Stream Network for Painter Classification of Highly-Varying Image Resolutions

Doron Nevo, Eli O. David, Nathan S. Netanyahu

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

3 Scopus citations

Abstract

Painter classification is a well-researched problem, which has been pursued mainly during the past two decades via traditional approaches of image processing and machine learning. In this paper, we propose a novel dual-stream architecture designed for capturing in parallel both global elements (e.g., scenery) and local structures (e.g., brushstrokes) in images of highly-varying resolutions and aspect ratios. Our proposed method yields 93.39% accuracy, which comprises an improvement of 1.66% (and an error rate reduction of 20%), compared to the previous state-of-the-art (SOTA) method on the same extensive dataset.

Original language	English
Title of host publication	Artificial Neural Networks and Machine Learning - ICANN 2022 - 31st International Conference on Artificial Neural Networks, Proceedings
Editors	Elias Pimenidis, Mehmet Aydin, Plamen Angelov, Chrisina Jayne, Antonios Papaleonidas
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	582-593
Number of pages	12
ISBN (Print)	9783031159367
DOIs	https://doi.org/10.1007/978-3-031-15937-4_49
State	Published - 2022
Event	31st International Conference on Artificial Neural Networks, ICANN 2022 - Bristol, United Kingdom Duration: 6 Sep 2022 → 9 Sep 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13532 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	31st International Conference on Artificial Neural Networks, ICANN 2022
Country/Territory	United Kingdom
City	Bristol
Period	6/09/22 → 9/09/22

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Funding

Nathan Netanyahu is also affiliated with the Department of Computer Science at the College of Law and Business, Ramat-Gan 5257346, Israel. D. Nevo—The support of the Israeli Innovation Authority and Defender Cyber Technologies LTD under File No. 69098 of the NOFAR Academic Knowledge Guidance Program is gratefully acknowledged.

Funders	Funder number
Israeli Innovation Authority and Defender Cyber Technologies LTD	69098

Keywords

Convolutional neural networks
Digital humanities
Image classification

Access to Document

10.1007/978-3-031-15937-4_49

Cite this

Nevo, D., David, E. O., & Netanyahu, N. S. (2022). DeepArtist: A Dual-Stream Network for Painter Classification of Highly-Varying Image Resolutions. In E. Pimenidis, M. Aydin, P. Angelov, C. Jayne, & A. Papaleonidas (Eds.), Artificial Neural Networks and Machine Learning - ICANN 2022 - 31st International Conference on Artificial Neural Networks, Proceedings (pp. 582-593). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13532 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-15937-4_49

Nevo, Doron ; David, Eli O. ; Netanyahu, Nathan S. / DeepArtist : A Dual-Stream Network for Painter Classification of Highly-Varying Image Resolutions. Artificial Neural Networks and Machine Learning - ICANN 2022 - 31st International Conference on Artificial Neural Networks, Proceedings. editor / Elias Pimenidis ; Mehmet Aydin ; Plamen Angelov ; Chrisina Jayne ; Antonios Papaleonidas. Springer Science and Business Media Deutschland GmbH, 2022. pp. 582-593 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Painter classification is a well-researched problem, which has been pursued mainly during the past two decades via traditional approaches of image processing and machine learning. In this paper, we propose a novel dual-stream architecture designed for capturing in parallel both global elements (e.g., scenery) and local structures (e.g., brushstrokes) in images of highly-varying resolutions and aspect ratios. Our proposed method yields 93.39\% accuracy, which comprises an improvement of 1.66\% (and an error rate reduction of 20\%), compared to the previous state-of-the-art (SOTA) method on the same extensive dataset.",

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Nevo, D, David, EO & Netanyahu, NS 2022, DeepArtist: A Dual-Stream Network for Painter Classification of Highly-Varying Image Resolutions. in E Pimenidis, M Aydin, P Angelov, C Jayne & A Papaleonidas (eds), Artificial Neural Networks and Machine Learning - ICANN 2022 - 31st International Conference on Artificial Neural Networks, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13532 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 582-593, 31st International Conference on Artificial Neural Networks, ICANN 2022, Bristol, United Kingdom, 6/09/22. https://doi.org/10.1007/978-3-031-15937-4_49

DeepArtist: A Dual-Stream Network for Painter Classification of Highly-Varying Image Resolutions. / Nevo, Doron; David, Eli O.; Netanyahu, Nathan S.
Artificial Neural Networks and Machine Learning - ICANN 2022 - 31st International Conference on Artificial Neural Networks, Proceedings. ed. / Elias Pimenidis; Mehmet Aydin; Plamen Angelov; Chrisina Jayne; Antonios Papaleonidas. Springer Science and Business Media Deutschland GmbH, 2022. p. 582-593 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13532 LNCS).

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

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Nevo D, David EO, Netanyahu NS. DeepArtist: A Dual-Stream Network for Painter Classification of Highly-Varying Image Resolutions. In Pimenidis E, Aydin M, Angelov P, Jayne C, Papaleonidas A, editors, Artificial Neural Networks and Machine Learning - ICANN 2022 - 31st International Conference on Artificial Neural Networks, Proceedings. Springer Science and Business Media Deutschland GmbH. 2022. p. 582-593. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-15937-4_49