| Records |
Author  |
Oriol Ramos Terrades; Ernest Valveny; Salvatore Tabbone |
| Title |
On the Combination of Ridgelets Descriptors for Symbol Recognition |
Type |
Book Chapter |
| Year |
2008 |
Publication |
Graphics Recognition: Recent Advances and New Oportunities, W. Lius, J. Llados, J.M. Ogier, LNCS 5046:104–113 |
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DAG |
Approved |
no |
| Call Number |
DAG @ dag @ RVT2008 |
Serial |
984 |
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| Author |
Oriol Ramos Terrades; Ernest Valveny; Salvatore Tabbone |
| Title |
Optimal Classifier Fusion in a Non-Bayesian Probabilistic Framework |
Type |
Journal Article |
| Year |
2009 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
| Volume |
31 |
Issue |
9 |
Pages |
1630–1644 |
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| Abstract |
The combination of the output of classifiers has been one of the strategies used to improve classification rates in general purpose classification systems. Some of the most common approaches can be explained using the Bayes' formula. In this paper, we tackle the problem of the combination of classifiers using a non-Bayesian probabilistic framework. This approach permits us to derive two linear combination rules that minimize misclassification rates under some constraints on the distribution of classifiers. In order to show the validity of this approach we have compared it with other popular combination rules from a theoretical viewpoint using a synthetic data set, and experimentally using two standard databases: the MNIST handwritten digit database and the GREC symbol database. Results on the synthetic data set show the validity of the theoretical approach. Indeed, results on real data show that the proposed methods outperform other common combination schemes. |
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0162-8828 |
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DAG |
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no |
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DAG @ dag @ RVT2009 |
Serial |
1220 |
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| Author |
Oriol Ramos Terrades; Ernest Valveny |
| Title |
Line Detection Using Ridgelets Transform for Graphic Symbol Representation |
Type |
Miscellaneous |
| Year |
2003 |
Publication |
In Pattern Recognition and Image Analysis, Lecture Notes in Computer Science 2652:829–837 |
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Springer-Verlag |
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DAG |
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no |
| Call Number |
DAG @ dag @ RaV2003a |
Serial |
403 |
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| Author |
Oriol Ramos Terrades; Ernest Valveny |
| Title |
Indexing Technical Symbols Using Ridgelets Transform |
Type |
Miscellaneous |
| Year |
2003 |
Publication |
Proceedings of the Fifth International Workshop on Graphics Recognition (GREC´03), 202–211 |
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DAG |
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no |
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DAG @ dag @ RaV2003c |
Serial |
405 |
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| Author |
Oriol Ramos Terrades; Ernest Valveny |
| Title |
Radon Transform for Lineal Symbol Representation |
Type |
Miscellaneous |
| Year |
2003 |
Publication |
Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR´03), 195–199 |
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DAG |
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no |
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DAG @ dag @ RaV2003d |
Serial |
406 |
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| Author |
Oriol Ramos Terrades; Ernest Valveny |
| Title |
Indexing Technical Symbols Using Ridgelets Transform |
Type |
Miscellaneous |
| Year |
2004 |
Publication |
Graphics Recognition: Recent Advances and Perspectives, J. Llados, Y.B. Kwon (Eds.), Lecture Notes in Computer Science, 3088:177–187, ISBN: 3–540–22478–5 |
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Springer-Verlag |
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DAG |
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no |
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DAG @ dag @ VaD2004c |
Serial |
503 |
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| Author |
Oriol Ramos Terrades; Ernest Valveny |
| Title |
A new use of the ridgelets transform for describing linear singularities in images |
Type |
Journal Article |
| Year |
2006 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
27 |
Issue |
6 |
Pages |
587–596 |
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DAG |
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no |
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DAG @ dag @ RaV2006a |
Serial |
635 |
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| Author |
Oriol Ramos Terrades; Ernest Valveny |
| Title |
Local Norm Features based on ridgelets Transform |
Type |
Miscellaneous |
| Year |
2005 |
Publication |
8th International Conference on Document Analysis and Recognition (ICDAR´05), 700–704 |
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DAG |
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no |
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DAG @ dag @ RaV2005d |
Serial |
642 |
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| Author |
Oriol Ramos Terrades; Alejandro Hector Toselli; Nicolas Serrano; Veronica Romero; Enrique Vidal; Alfons Juan |
| Title |
Interactive layout analysis and transcription systems for historic handwritten documents |
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Conference Article |
| Year |
2010 |
Publication |
10th ACM Symposium on Document Engineering |
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Pages |
219–222 |
| Keywords |
Handwriting recognition; Interactive predictive processing; Partial supervision; Interactive layout analysis |
| Abstract |
The amount of digitized legacy documents has been rising dramatically over the last years due mainly to the increasing number of on-line digital libraries publishing this kind of documents, waiting to be classified and finally transcribed into a textual electronic format (such as ASCII or PDF). Nevertheless, most of the available fully-automatic applications addressing this task are far from being perfect and heavy and inefficient human intervention is often required to check and correct the results of such systems. In contrast, multimodal interactive-predictive approaches may allow the users to participate in the process helping the system to improve the overall performance. With this in mind, two sets of recent advances are introduced in this work: a novel interactive method for text block detection and two multimodal interactive handwritten text transcription systems which use active learning and interactive-predictive technologies in the recognition process. |
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Manchester, United Kingdom |
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ACM |
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DAG |
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no |
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Admin @ si @RTS2010 |
Serial |
1857 |
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| Author |
Oriol Ramos Terrades; Albert Berenguel; Debora Gil |
| Title |
A flexible outlier detector based on a topology given by graph communities |
Type |
Miscellaneous |
| Year |
2020 |
Publication |
Arxiv |
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Outlier, or anomaly, detection is essential for optimal performance of machine learning methods and statistical predictive models. It is not just a technical step in a data cleaning process but a key topic in many fields such as fraudulent document detection, in medical applications and assisted diagnosis systems or detecting security threats. In contrast to population-based methods, neighborhood based local approaches are simple flexible methods that have the potential to perform well in small sample size unbalanced problems. However, a main concern of local approaches is the impact that the computation of each sample neighborhood has on the method performance. Most approaches use a distance in the feature space to define a single neighborhood that requires careful selection of several parameters. This work presents a local approach based on a local measure of the heterogeneity of sample labels in the feature space considered as a topological manifold. Topology is computed using the communities of a weighted graph codifying mutual nearest neighbors in the feature space. This way, we provide with a set of multiple neighborhoods able to describe the structure of complex spaces without parameter fine tuning. The extensive experiments on real-world data sets show that our approach overall outperforms, both, local and global strategies in multi and single view settings. |
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IAM; DAG; 600.139; 600.145; 600.140; 600.121 |
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no |
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Admin @ si @ RBG2020 |
Serial |
3475 |
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| Author |
Oriol Ramos Terrades; Albert Berenguel; Debora Gil |
| Title |
A Flexible Outlier Detector Based on a Topology Given by Graph Communities |
Type |
Journal Article |
| Year |
2022 |
Publication |
Big Data Research |
Abbreviated Journal |
BDR |
| Volume |
29 |
Issue |
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Pages |
100332 |
| Keywords |
Classification algorithms; Detection algorithms; Description of feature space local structure; Graph communities; Machine learning algorithms; Outlier detectors |
| Abstract |
Outlier detection is essential for optimal performance of machine learning methods and statistical predictive models. Their detection is especially determinant in small sample size unbalanced problems, since in such settings outliers become highly influential and significantly bias models. This particular experimental settings are usual in medical applications, like diagnosis of rare pathologies, outcome of experimental personalized treatments or pandemic emergencies. In contrast to population-based methods, neighborhood based local approaches compute an outlier score from the neighbors of each sample, are simple flexible methods that have the potential to perform well in small sample size unbalanced problems. A main concern of local approaches is the impact that the computation of each sample neighborhood has on the method performance. Most approaches use a distance in the feature space to define a single neighborhood that requires careful selection of several parameters, like the number of neighbors.
This work presents a local approach based on a local measure of the heterogeneity of sample labels in the feature space considered as a topological manifold. Topology is computed using the communities of a weighted graph codifying mutual nearest neighbors in the feature space. This way, we provide with a set of multiple neighborhoods able to describe the structure of complex spaces without parameter fine tuning. The extensive experiments on real-world and synthetic data sets show that our approach outperforms, both, local and global strategies in multi and single view settings. |
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August 28, 2022 |
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DAG; IAM; 600.140; 600.121; 600.139; 600.145; 600.159 |
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no |
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Admin @ si @ RBG2022a |
Serial |
3718 |
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| Author |
Oriol Ramos Terrades |
| Title |
Descripcio i classificacio de simbols tecnics usant la transformada de crestetes |
Type |
Report |
| Year |
2003 |
Publication |
CVC Technical Report #74 |
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CVC (UAB) |
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DAG |
Approved |
no |
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DAG @ dag @ Ram2003 |
Serial |
517 |
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| Author |
Oriol Ramos Terrades |
| Title |
Linear Combination of Multiresolution Descriptors: Application to Graphics Recognition |
Type |
Book Whole |
| Year |
2006 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC & Universite Nancy 2 |
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Ph.D. thesis |
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Editor |
Salvatore Antoine Tabbone;Ernest Valveny |
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DAG |
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no |
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DAG @ dag @ Ram2006 |
Serial |
713 |
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| Author |
Oriol Pujol; Sergio Escalera; Petia Radeva |
| Title |
An Incremental Node Embedding Technique for Error Correcting Output Codes |
Type |
Journal |
| Year |
2008 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
41 |
Issue |
2 |
Pages |
713–725 |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ PER2008 |
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942 |
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| Author |
Oriol Pujol; Petia Radeva; Jordi Vitria; J. Mauri |
| Title |
Adaboost to Classify Plaque Appearance in IVUS Images |
Type |
Miscellaneous |
| Year |
2004 |
Publication |
Progress in Pattern Recognition, Image Analysis and Applications, LNCS 3287:629–636 |
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Puebla (Mexico) |
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OR;MILAB;HuPBA;MV |
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no |
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BCNPCL @ bcnpcl @ PRV2004 |
Serial |
472 |
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