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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
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Title |
Vocabulary Selection for Graph of Words Embedding |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
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Volume |
6669 |
Issue |
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Pages |
216-223 |
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Abstract |
The Graph of Words Embedding consists in mapping every graph in a given dataset to a feature vector by counting unary and binary relations between node attributes of the graph. It has been shown to perform well for graphs with discrete label alphabets. In this paper we extend the methodology to graphs with n-dimensional continuous attributes by selecting node representatives. We propose three different discretization procedures for the attribute space and experimentally evaluate the dependence on both the selector and the number of node representatives. In the context of graph classification, the experimental results reveal that on two out of three public databases the proposed extension achieves superior performance over a standard reference system. |
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Las Palmas de Gran Canaria. Spain |
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Springer |
Place of Publication |
Berlin |
Editor |
Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario |
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978-3-642-21256-7 |
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Conference |
IbPRIA |
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DAG |
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no |
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Call Number |
Admin @ si @ GVB2011b |
Serial |
1744 |
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Author |
Hana Jarraya; Muhammad Muzzamil Luqman; Jean-Yves Ramel |
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Title |
Improving Fuzzy Multilevel Graph Embedding Technique by Employing Topological Node Features: An Application to Graphics Recognition |
Type |
Book Chapter |
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Year |
2017 |
Publication |
Graphics Recognition. Current Trends and Challenges |
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Volume |
9657 |
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Springer |
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Editor |
B. Lamiroy; R Dueire Lins |
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Conference |
GREC |
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Notes |
DAG; 600.097; 600.121 |
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no |
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Call Number |
Admin @ si @ JLR2017 |
Serial |
2928 |
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Author |
Arnau Baro; Pau Riba; Jorge Calvo-Zaragoza; Alicia Fornes |
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Title |
Optical Music Recognition by Long Short-Term Memory Networks |
Type |
Book Chapter |
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Year |
2018 |
Publication |
Graphics Recognition. Current Trends and Evolutions |
Abbreviated Journal |
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Volume |
11009 |
Issue |
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Pages |
81-95 |
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Keywords |
Optical Music Recognition; Recurrent Neural Network; Long ShortTerm Memory |
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Abstract |
Optical Music Recognition refers to the task of transcribing the image of a music score into a machine-readable format. Many music scores are written in a single staff, and therefore, they could be treated as a sequence. Therefore, this work explores the use of Long Short-Term Memory (LSTM) Recurrent Neural Networks for reading the music score sequentially, where the LSTM helps in keeping the context. For training, we have used a synthetic dataset of more than 40000 images, labeled at primitive level. The experimental results are promising, showing the benefits of our approach. |
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Springer |
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Editor |
A. Fornes, B. Lamiroy |
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ISBN |
978-3-030-02283-9 |
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Conference |
GREC |
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Notes |
DAG; 600.097; 601.302; 601.330; 600.121 |
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no |
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Call Number |
Admin @ si @ BRC2018 |
Serial |
3227 |
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Author |
Lluis Gomez; Anguelos Nicolaou; Marçal Rusiñol; Dimosthenis Karatzas |
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Title |
12 years of ICDAR Robust Reading Competitions: The evolution of reading systems for unconstrained text understanding |
Type |
Book Chapter |
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Year |
2020 |
Publication |
Visual Text Interpretation – Algorithms and Applications in Scene Understanding and Document Analysis |
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Springer |
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Editor |
K. Alahari; C.V. Jawahar |
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Series on Advances in Computer Vision and Pattern Recognition |
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Notes |
DAG; 600.121 |
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no |
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Call Number |
GNR2020 |
Serial |
3494 |
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Author |
Lluis Gomez; Dena Bazazian; Dimosthenis Karatzas |
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Title |
Historical review of scene text detection research |
Type |
Book Chapter |
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Year |
2020 |
Publication |
Visual Text Interpretation – Algorithms and Applications in Scene Understanding and Document Analysis |
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Publisher |
Springer |
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Editor |
K. Alahari; C.V. Jawahar |
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Series on Advances in Computer Vision and Pattern Recognition |
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Notes |
DAG; 600.121 |
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no |
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Call Number |
Admin @ si @ GBK2020 |
Serial |
3495 |
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Author |
Jon Almazan; Lluis Gomez; Suman Ghosh; Ernest Valveny; Dimosthenis Karatzas |
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Title |
WATTS: A common representation of word images and strings using embedded attributes for text recognition and retrieval |
Type |
Book Chapter |
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Year |
2020 |
Publication |
Visual Text Interpretation – Algorithms and Applications in Scene Understanding and Document Analysis |
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Publisher |
Springer |
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Editor |
Analysis”, K. Alahari; C.V. Jawahar |
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Series on Advances in Computer Vision and Pattern Recognition |
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Notes |
DAG; 600.121 |
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no |
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Call Number |
Admin @ si @ AGG2020 |
Serial |
3496 |
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Author |
Utkarsh Porwal; Alicia Fornes; Faisal Shafait (eds) |
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Title |
Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition. 18th International Conference, ICFHR 2022 |
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Book Whole |
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Year |
2022 |
Publication |
Frontiers in Handwriting Recognition. |
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Volume |
13639 |
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Address |
ICFHR 2022, Hyderabad, India, December 4–7, 2022 |
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Publisher |
Springer |
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Editor |
Utkarsh Porwal; Alicia Fornes; Faisal Shafait |
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Edition |
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ISBN |
978-3-031-21648-0 |
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Conference |
ICFHR |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ PFS2022 |
Serial |
3809 |
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Author |
Salim Jouili; Salvatore Tabbone; Ernest Valveny |
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Title |
Comparing Graph Similarity Measures for Graphical Recognition |
Type |
Book Chapter |
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Year |
2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
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Volume |
6020 |
Issue |
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Pages |
37-48 |
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Abstract |
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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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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Series Volume |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-13727-3 |
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Conference |
GREC |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ JTV2010 |
Serial |
2404 |
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Author |
Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados |
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Title |
Improving Fuzzy Multilevel Graph Embedding through Feature Selection Technique |
Type |
Conference Article |
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Year |
2012 |
Publication |
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop |
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Volume |
7626 |
Issue |
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Pages |
243-253 |
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Abstract |
Graphs are the most powerful, expressive and convenient data structures but there is a lack of efficient computational tools and algorithms for processing them. The embedding of graphs into numeric vector spaces permits them to access the state-of-the-art computational efficient statistical models and tools. In this paper we take forward our work on explicit graph embedding and present an improvement to our earlier proposed method, named “fuzzy multilevel graph embedding – FMGE”, through feature selection technique. FMGE achieves the embedding of attributed graphs into low dimensional vector spaces by performing a multilevel analysis of graphs and extracting a set of global, structural and elementary level features. Feature selection permits FMGE to select the subset of most discriminating features and to discard the confusing ones for underlying graph dataset. Experimental results for graph classification experimentation on IAM letter, GREC and fingerprint graph databases, show improvement in the performance of FMGE. |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-34165-6 |
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Conference |
SSPR&SPR |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ LRL2012 |
Serial |
2381 |
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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 |
Type |
Conference Article |
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Year |
2009 |
Publication |
7th IAPR – TC–15 Workshop on Graph–Based Representations in Pattern Recognition |
Abbreviated Journal |
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Volume |
5534 |
Issue |
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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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Address |
Venice, Italy |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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Series Volume |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-02123-7 |
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Conference |
GBR |
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Notes |
DAG |
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no |
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Call Number |
DAG @ dag @ FKV2009 |
Serial |
1173 |
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