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| Author | Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman | ||||
| Title | A Performance Characterization Algorithm for Symbol Localization | Type | Book Chapter | ||
| Year | 2010 | Publication | Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers | Abbreviated Journal | |
Volume  |
6020 | Issue | Pages | 260–271 | |
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| Abstract | 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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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-13727-3 | Medium | |
| Area | Expedition | Conference | GREC | ||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ DRV2010 | Serial | 2406 | ||
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| Author | Marçal Rusiñol; K. Bertet; Jean-Marc Ogier; Josep Llados | ||||
| Title | Symbol Recognition Using a Concept Lattice of Graphical Patterns | Type | Book Chapter | ||
| Year | 2010 | Publication | Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers | Abbreviated Journal | |
| Volume |
6020 | Issue | Pages | 187-198 | |
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| Abstract | 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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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-13727-3 | Medium | |
| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ RBO2010 | Serial | 2407 | ||
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| Author | Partha Pratim Roy; Umapada Pal; Josep Llados | ||||
| Title | Touching Text Character Localization in Graphical Documents using SIFT | Type | Book Chapter | ||
| Year | 2010 | Publication | Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers | Abbreviated Journal | |
| Volume |
6020 | Issue | Pages | 199-211 | |
| Keywords | Support Vector Machine; Text Component; Graphical Line; Document Image; Scale Invariant Feature Transform | ||||
| Abstract | Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult.
Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches. |
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-13727-3 | Medium | |
| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ RPL2010c | Serial | 2408 | ||
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| Author | Santiago Segui; Laura Igual; Jordi Vitria | ||||
| Title | Weighted Bagging for Graph based One-Class Classifiers | Type | Conference Article | ||
| Year | 2010 | Publication | 9th International Workshop on Multiple Classifier Systems | Abbreviated Journal | |
| Volume |
5997 | Issue | Pages | 1-10 | |
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| Abstract | Most conventional learning algorithms require both positive and negative training data for achieving accurate classification results. However, the problem of learning classifiers from only positive data arises in many applications where negative data are too costly, difficult to obtain, or not available at all. Minimum Spanning Tree Class Descriptor (MSTCD) was presented as a method that achieves better accuracies than other one-class classifiers in high dimensional data. However, the presence of outliers in the target class severely harms the performance of this classifier. In this paper we propose two bagging strategies for MSTCD that reduce the influence of outliers in training data. We show the improved performance on both real and artificially contaminated data. | ||||
| Address | Cairo, Egypt | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-12126-5 | Medium | |
| Area | Expedition | Conference | MCS | ||
| Notes | MILAB;OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ SIV2010 | Serial | 1284 | ||
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| Author | Mirko Arnold; Anarta Ghosh; Stephen Ameling; G Lacey | ||||
| Title | Automatic segmentation and inpainting of specular highlights for endoscopic imaging | Type | Journal Article | ||
| Year | 2010 | Publication | EURASIP Journal on Image and Video Processing | Abbreviated Journal | EURASIP JIVP |
| Volume |
2010 | Issue | 9 | Pages | |
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| Area | 800 | Expedition | Conference | ||
| Notes | MV | Approved | no | ||
| Call Number | fernando @ fernando @ | Serial | 2423 | ||
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| Author | Sergio Escalera; Oriol Pujol; Eric Laciar; Jordi Vitria; Esther Pueyo; Petia Radeva | ||||
| Title | Classification of Coronary Damage in Chronic Chagasic Patients | Type | Book Chapter | ||
| Year | 2010 | Publication | Intelligent Systems – From Theory to Practice. Studies in Computational Intelligence | Abbreviated Journal | |
| Volume |
299 | Issue | Pages | 461-478 | |
| Keywords | Chagas disease; Error-Correcting Output Codes; High resolution ECG; Decoding | ||||
| Abstract | Post Conference IEEE-IS 2008
The Chagas’ disease is endemic in all Latin America, affecting millions of people in the continent. In order to diagnose and treat the chagas’ disease, it is important to detect and measure the coronary damage of the patient. In this paper, we analyze and categorize patients into different groups based on the coronary damage produced by the disease. Based on the features of the heart cycle extracted using high resolution ECG, a multi-class scheme of Error-Correcting Output Codes (ECOC)is formulated and successfully applied. The results show that the proposed scheme obtains significant performance improvements compared to previous works and state-of-the-art ECOC designs. |
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| Publisher | Springer-Verlag | Place of Publication | Editor | V. Sgurev, M. Hadjiski (eds) | |
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| Area | Expedition | Conference | |||
| Notes | OR;MILAB;HUPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPL2010 | Serial | 1452 | ||
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| Author | David Aldavert; Arnau Ramisa; Ramon Lopez de Mantaras; Ricardo Toledo | ||||
| Title | Real-time Object Segmentation using a Bag of Features Approach | Type | Conference Article | ||
| Year | 2010 | Publication | 13th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume |
220 | Issue | Pages | 321–329 | |
| Keywords | Object Segmentation; Bag Of Features; Feature Quantization; Densely sampled descriptors | ||||
| Abstract | In this paper, we propose an object segmentation framework, based on the popular bag of features (BoF), which can process several images per second while achieving a good segmentation accuracy assigning an object category to every pixel of the image. We propose an efficient color descriptor to complement the information obtained by a typical gradient-based local descriptor. Results show that color proves to be a useful cue to increase the segmentation accuracy, specially in large homogeneous regions. Then, we extend the Hierarchical K-Means codebook using the recently proposed Vector of Locally Aggregated Descriptors method. Finally, we show that the BoF method can be easily parallelized since it is applied locally, thus the time necessary to process an image is further reduced. The performance of the proposed method is evaluated in the standard PASCAL 2007 Segmentation Challenge object segmentation dataset. | ||||
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| Publisher | IOS Press Amsterdam, | Place of Publication | Editor | In R.Alquezar, A.Moreno, J.Aguilar. | |
| Language | Summary Language | Original Title | |||
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| ISSN | ISBN | 9781607506423 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ ARL2010b | Serial | 1417 | ||
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| Author | Eloi Puertas; Sergio Escalera; Oriol Pujol | ||||
| Title | Classifying Objects at Different Sizes with Multi-Scale Stacked Sequential Learning | Type | Conference Article | ||
| Year | 2010 | Publication | 13th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume |
220 | Issue | Pages | 193–200 | |
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| Abstract | Sequential learning is that discipline of machine learning that deals with dependent data. In this paper, we use the Multi-scale Stacked Sequential Learning approach (MSSL) to solve the task of pixel-wise classification based on contextual information. The main contribution of this work is a shifting technique applied during the testing phase that makes possible, thanks to template images, to classify objects at different sizes. The results show that the proposed method robustly classifies such objects capturing their spatial relationships. | ||||
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| Publisher | Place of Publication | Editor | R. Alquezar, A. Moreno, J. Aguilar | ||
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| ISSN | ISBN | 978-1-60750-642-3 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | HUPBA;MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ PEP2010 | Serial | 1448 | ||
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| Author | Sergio Vera | ||||
| Title | Finger joint modelling from hand X-ray images for assessing rheumatoid arthritis | Type | Report | ||
| Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume |
164 | Issue | Pages | ||
| Keywords | Rheumatoid arthritis; joint detection; X-ray; Van der Heijde score | ||||
| Abstract | Rheumatoid arthritis is an autoimmune, systemic, inflammatory disorder that mainly af- fects bone joints. While there is no cure for this disease, continuous advances on palliative treatments require frequent verification of patient’s illness evolution. Such evolution is mea- sured through several available semi-quantitative methods that require evaluation of hand and foot X-ray images. Accurate assessment is a time consuming task that requires highly trained personnel. This hinders a generalized use in clinical practice for early diagnose and disease follow-up. In the context of the automatization of such evaluation methods we present a method for detection and characterization of finger joints in hand radiography images. Several measures for assessing the reduction of joint space width are proposed. We compare for the first time such measures to the Van der Heijde score, the gold standard method for rheumatoid arthritis assessment. The proposed method outperforms existing strategies with a detection rate above 95%. Our comparison to Van der Heijde index shows a promising correlation that encourages further research. | ||||
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| Corporate Author | Thesis | Master's thesis | |||
| Publisher | Place of Publication | Bellaterra 01893, Barcelona, Spain | Editor | ||
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| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ Ver2010 | Serial | 1661 | ||
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| Author | Jon Almazan | ||||
| Title | Deforming the Blurred Shape Model for Shape Description and Recognition | Type | Report | ||
| Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume |
163 | Issue | Pages | ||
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| Corporate Author | Thesis | Master's thesis | |||
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| Notes | Approved | no | |||
| Call Number | Admin @ si @ Alm2010 | Serial | 1354 | ||
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| Author | Monica Piñol | ||||
| Title | Adaptative Vocabulary Tree for Image Classification using Reinforcement Learning | Type | Report | ||
| Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume |
162 | Issue | Pages | ||
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| Address | Bellaterra (Barcelona) | ||||
| Corporate Author | Computer Vision Center | Thesis | Master's thesis | ||
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| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ Piñ2010 | Serial | 1936 | ||
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| Author | David Fernandez | ||||
| Title | Handwritten Word Spotting in Old Manuscript Images using Shape Descriptors | Type | Report | ||
| Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume |
161 | Issue | Pages | ||
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| Corporate Author | Thesis | Master's thesis | |||
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| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ Fer2010b | Serial | 1353 | ||
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| Author | Ekain Artola | ||||
| Title | Human Attention Map Prediction Combining Visual Features | Type | Report | ||
| Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume |
160 | Issue | Pages | ||
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| Corporate Author | Thesis | Bachelor's thesis | |||
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| Notes | Approved | no | |||
| Call Number | Admin @ si @ Art2010 | Serial | 1352 | ||
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| Author | Anjan Dutta | ||||
| Title | Symbol Spotting in Graphical Documents by Serialized Subgraph Matching | Type | Report | ||
| Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume |
159 | Issue | Pages | ||
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| Corporate Author | Thesis | Master's thesis | |||
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| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ Dut2010 | Serial | 1351 | ||
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| Author | Lluis Pere de las Heras | ||||
| Title | Syntactic Model for Semantic Document Analysis | Type | Report | ||
| Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume |
158 | Issue | Pages | ||
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| Notes | Approved | no | |||
| Call Number | Admin @ si @ Per2010 | Serial | 1350 | ||
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