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Author |
W. Liu; Josep Llados |
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Title |
Graphics Recognition. Ten Years Review and Future Perspectives |
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Year |
2006 |
Publication  |
6th International Workshop |
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3926 |
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Hong Kong (China) |
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GREC |
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no |
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Call Number |
DAG @ dag @ LiL2006 |
Serial |
800 |
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Author |
Miquel Ferrer; Dimosthenis Karatzas; Ernest Valveny; Horst Bunke |
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Title |
A Recursive Embedding Approach to Median Graph Computation |
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Conference Article |
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Year |
2009 |
Publication |
7th IAPR – TC–15 Workshop on Graph–Based Representations in Pattern Recognition |
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Volume |
5534 |
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Pages |
113–123 |
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Abstract |
The median graph has been shown to be a good choice to infer a representative of a set of graphs. It has been successfully applied to graph-based classification and clustering. Nevertheless, its computation is extremely complex. Several approaches have been presented up to now based on different strategies. In this paper we present a new approximate recursive algorithm for median graph computation based on graph embedding into vector spaces. Preliminary experiments on three databases show that this new approach is able to obtain better medians than the previous existing approaches. |
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Venice, Italy |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-02123-7 |
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GBR |
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no |
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Call Number |
DAG @ dag @ FKV2009 |
Serial |
1173 |
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Author |
Mohamed Ali Souibgui; Pau Torras; Jialuo Chen; Alicia Fornes |
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Title |
An Evaluation of Handwritten Text Recognition Methods for Historical Ciphered Manuscripts |
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Conference Article |
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Year |
2023 |
Publication |
7th International Workshop on Historical Document Imaging and Processing |
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7-12 |
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This paper investigates the effectiveness of different deep learning HTR families, including LSTM, Seq2Seq, and transformer-based approaches with self-supervised pretraining, in recognizing ciphered manuscripts from different historical periods and cultures. The goal is to identify the most suitable method or training techniques for recognizing ciphered manuscripts and to provide insights into the challenges and opportunities in this field of research. We evaluate the performance of these models on several datasets of ciphered manuscripts and discuss their results. This study contributes to the development of more accurate and efficient methods for recognizing historical manuscripts for the preservation and dissemination of our cultural heritage. |
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HIP |
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Call Number |
Admin @ si @ STC2023 |
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3849 |
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Author |
Liu Wenyin; Josep Llados; Jean-Marc Ogier |
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Title |
Graphics Recognition. Recent Advances and New Opportunities. |
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Book Whole |
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Year |
2008 |
Publication |
7th International Workshop, Selected Papers, |
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5046 |
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Address |
Curitiba (Brazil) |
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978-3-540-88184-1 |
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GREC |
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DAG |
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no |
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Call Number |
DAG @ dag @ WLO2008 |
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1012 |
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Author |
N. Zakaria; Jean-Marc Ogier; Josep Llados |
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Title |
The Fuzzy-Spatial Descriptor for the Online Graphic Recognition: Overlapping Matrix Algorithm |
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Book Chapter |
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2006 |
Publication |
7th International Workshop, Document Analysis Systems VII (DAS´06), LNCS 3872: 616–627 |
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Nelson (New Zealand) |
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DAG |
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no |
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Call Number |
DAG @ dag @ ZOL2006 |
Serial |
629 |
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Author |
Joan Mas; Gemma Sanchez; Josep Llados |
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Title |
SSP: Sketching slide Presentations, a Syntactic Approach |
Type |
Conference Article |
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Year |
2009 |
Publication |
8th IAPR International Workshop on Graphics Recognition |
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The design of a slide presentation is a creative process. In this process first, humans visualize in their minds what they want to explain. Then, they have to be able to represent this knowledge in an understandable way. There exists a lot of commercial software that allows to create our own slide presentations but the creativity of the user is rather limited. In this article we present an application that allows the user to create and visualize a slide presentation from a sketch. A slide may be seen as a graphical document or a diagram where its elements are placed in a particular spatial arrangement. To describe and recognize slides a syntactic approach is proposed. This approach is based on an Adjacency Grammar and a parsing methodology to cope with this kind of grammars. The experimental evaluation shows the performance of our methodology from a qualitative and a quantitative point of view. Six different slides containing different number of symbols, from 4 to 7, have been given to the users and they have drawn them without restrictions in the order of the elements. The quantitative results give an idea on how suitable is our methodology to describe and recognize the different elements in a slide. |
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Address |
La Rochelle; France; July 2009 |
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GREC |
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DAG |
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no |
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Call Number |
DAG @ dag @ MSL2009a |
Serial |
1441 |
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Author |
S.Jouili; Salvatore Tabbone; Ernest Valveny |
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Title |
Comparing Graph Similarity Measures for Graphical Recognition. |
Type |
Conference Article |
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Year |
2009 |
Publication |
8th IAPR International Workshop on Graphics Recognition |
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In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used including line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each graph distance measure depends on the kind of data and the graph representation technique. |
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La Rochelle; France; July 2009 |
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Springer |
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GREC |
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DAG |
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Call Number |
DAG @ dag @ JTV2009 |
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1442 |
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Author |
Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman |
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Title |
A Performance Characterization Algorithm for Symbol Localization |
Type |
Conference Article |
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Year |
2009 |
Publication |
8th IAPR International Workshop on Graphics Recognition |
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Pages |
3-11 |
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In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols). |
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La Rochelle; July 2009 |
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Springer |
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GREC |
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DAG |
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Call Number |
DAG @ dag @ DRV2009 |
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1443 |
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Author |
Marçal Rusiñol; K. Bertet; Jean-Marc Ogier; Josep Llados |
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Title |
Symbol Recognition Using a Concept Lattice of Graphical Patterns |
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Conference Article |
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Year |
2009 |
Publication |
8th IAPR International Workshop on Graphics Recognition |
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In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest. |
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La Rochelle; July 2009 |
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GREC |
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DAG |
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Call Number |
DAG @ dag @ RBO2009 |
Serial |
1444 |
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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
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Title |
Dimensionality Reduction for Graph of Words Embedding |
Type |
Conference Article |
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Year |
2011 |
Publication |
8th IAPR-TC-15 International Workshop. Graph-Based Representations in Pattern Recognition |
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6658 |
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Pages |
22-31 |
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Abstract |
The Graph of Words Embedding consists in mapping every graph of a given dataset to a feature vector by counting unary and binary relations between node attributes of the graph. While it shows good properties in classification problems, it suffers from high dimensionality and sparsity. These two issues are addressed in this article. Two well-known techniques for dimensionality reduction, kernel principal component analysis (kPCA) and independent component analysis (ICA), are applied to the embedded graphs. We discuss their performance compared to the classification of the original vectors on three different public databases of graphs. |
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Münster, Germany |
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Xiaoyi Jiang; Miquel Ferrer; Andrea Torsello |
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978-3-642-20843-0 |
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GbRPR |
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Admin @ si @ GVB2011a |
Serial |
1743 |
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