Record link: 
http://hdl.handle.net/20.500.12708/150315
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Title: 
Self-supervised Vision Transformers with Data Augmentation Strategies Using Morphological Operations for Writer Retrieval
en
Citation: 
Peer, M., Kleber, F., & Sablatnig, R. (2022). Self-supervised Vision Transformers with Data Augmentation Strategies Using Morphological Operations for Writer Retrieval. In Frontiers in Handwriting Recognition: 18th International Conference, ICFHR 2022, Hyderabad, India, December 4–7, 2022, Proceedings (pp. 122–136). https://doi.org/10.1007/978-3-031-21648-0_9
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Publisher DOI: 
10.1007/978-3-031-21648-0_9
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Peer, Marco 
Kleber, Florian 
Sablatnig, Robert 
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Organisational Unit: 
E193-01 - Forschungsbereich Computer Vision 
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Published in: 
Frontiers in Handwriting Recognition: 18th International Conference, ICFHR 2022, Hyderabad, India, December 4–7, 2022, Proceedings 
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ISBN: 
978-3-031-21648-0
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Volume: 
13639
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Date (published): 
2022
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Event name: 
Frontiers in Handwriting Recognition: 18th International Conference, ICFHR 2022 
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Event date: 
4-Dec-2022 - 7-Dec-2022
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Event place: 
Hyderabad, India
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Number of Pages: 
15
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Peer reviewed: 
Yes
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Keywords: 
Writer Retrieval
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Self-supervised Learning; Document Analysis; Document Retrieval; Vision Transformer
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Project title: 
IT unterstützte Suche und Vergleich von Handschriften: 879687 (FFG - Österr. Forschungsförderungs- gesellschaft mbH) 
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Link (external): 
https://icfhr2022.org/cfp.php
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Research Areas: 
Visual Computing and Human-Centered Technology: 100%
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Science Branch: 
1020 - Informatik: 90%
1010 - Mathematik: 10%
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Appears in Collections:
Conference Paper

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