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Robert Sablatnig
Researcher at Vienna University of Technology
Publications - 205
Citations - 3030
Robert Sablatnig is an academic researcher from Vienna University of Technology. The author has contributed to research in topics: Image segmentation & Multispectral image. The author has an hindex of 27, co-authored 194 publications receiving 2654 citations. Previous affiliations of Robert Sablatnig include University of Vienna & University of Engineering and Technology, Peshawar.
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Journal ArticleDOI
Transforming scholarship in the archives through handwritten text recognition: Transkribus as a case study
Guenter Muehlberger,Louise Seaward,Melissa Terras,Sofia Ares Oliveira,Vicente Bosch,M. Bryan,Sebastian Colutto,Hervé Déjean,Markus Diem,Stefan Fiel,Basilis Gatos,Albert Greinoecker,Tobias Grüning,Guenter Hackl,Vili Haukkovaara,Gerhard Heyer,Lauri Hirvonen,Tobias Hodel,Matti Jokinen,Philip Kahle,Mario Kallio,Frédéric Kaplan,Florian Kleber,Roger Labahn,Eva Lang,Sören Laube,Gundram Leifert,Georgios Louloudis,Rory McNicholl,Jean-Luc Meunier,Johannes Michael,Elena Mühlbauer,Nathanael Philipp,Ioannis Pratikakis,Joan Puigcerver Pérez,Hannelore Putz,George Retsinas,Verónica Romero,Robert Sablatnig,Joan Andreu Sánchez,Philip Schofield,Giorgos Sfikas,Christian Sieber,Nikolaos Stamatopoulos,Tobias Strauß,Tamara Terbul,Alejandro Héctor Toselli,Berthold Ulreich,Mauricio Villegas,Enrique Vidal,Johanna Walcher,Max Weidemann,Herbert Wurster,Konstantinos Zagoris +53 more
TL;DR: An overview of the current use of handwritten text recognition (HTR) on archival manuscript material, as provided by the EU H2020 funded Transkribus platform, can be found in this article.
Proceedings ArticleDOI
ICFHR 2014 Competition on Handwritten Digit String Recognition in Challenging Datasets (HDSRC 2014)
Markus Diem,Stefan Fiel,Florian Kleber,Robert Sablatnig,Jose M. Saavedra,David Contreras,Juan Manuel Barrios,Luiz S. Oliveira +7 more
TL;DR: This paper presents the results of the HDSRC 2014 competition on handwritten digit string recognition in challenging datasets organized in conjunction with ICFHR 2014 and introduces two new challenging datasets for benchmarking.
Journal ArticleDOI
An automated pottery archival and reconstruction system
Martin Kampel,Robert Sablatnig +1 more
TL;DR: An automated archival system for archaeological classification and reconstruction of ceramics uses the profile of an archaeological fragment, which is the cross-section of the fragment in the direction of the rotational axis of symmetry, to classify and reconstruct it virtually.
Journal Article
Computer based acquisition of archaeological finds: the first step towards automatic classification
Robert Sablatnig,Ch. Menard +1 more
TL;DR: Two acquisirion methods for archaeological finds are proposed forming the first step towards automatic classification, that could help archaeologist in his work.
Proceedings ArticleDOI
End-to-End Text Recognition Using Local Ternary Patterns, MSER and Deep Convolutional Nets
TL;DR: The system presented outperforms state of the art methods on the ICDAR 2003 dataset in the text-detection, dictionary-driven cropped-word recognition and Dictionary-driven end-to-end recognition tasks.