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Alicia Fornés
Researcher at Autonomous University of Barcelona
Publications - 141
Citations - 3162
Alicia Fornés is an academic researcher from Autonomous University of Barcelona. The author has contributed to research in topics: Handwriting recognition & Language model. The author has an hindex of 26, co-authored 133 publications receiving 2494 citations. Previous affiliations of Alicia Fornés include University of Valencia.
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Journal ArticleDOI
Word Spotting and Recognition with Embedded Attributes
TL;DR: An approach in which both word images and text strings are embedded in a common vectorial subspace, allowing one to cast recognition and retrieval tasks as a nearest neighbor problem and is very fast to compute and, especially, to compare.
Proceedings ArticleDOI
Transcription alignment of Latin manuscripts using hidden Markov models
TL;DR: The Saint Gall database is introduced that includes images as well as the transcription of a Latin manuscript from the 9th century written in Carolingian script and it is demonstrated that a considerable alignment accuracy can be achieved, even with weakly trained character models.
Journal ArticleDOI
The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition
Verónica Romero,Alicia Fornés,Nicolás Serrano,Joan Andreu Sánchez,Alejandro Héctor Toselli,Volkmar Frinken,Enrique Vidal,Josep Lladós +7 more
TL;DR: A new database is presented, compiled from a marriage license books collection, to support research in automatic handwriting recognition for historical documents containing social records, and about the capability of state-of-the-art handwritten text recognition systems, when applied to the presented database.
Journal ArticleDOI
CVC-MUSCIMA: a ground truth of handwritten music score images for writer identification and staff removal
TL;DR: This paper presents the CVC-MUSCIMA database and ground truth of handwritten music score images, especially designed for writer identification and staff removal tasks and provides some baseline results for easing the comparison between different approaches.
Journal ArticleDOI
Blurred Shape Model for binary and grey-level symbol recognition
TL;DR: A symbol shape description to deal with the changes in appearance that these types of symbols suffer, and the Blurred Shape Model descriptor (BSM), where new features encode the probability of appearance of each pixel that outlines the symbols shape.