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Author |
Angel Sappa; Boris X. Vintimilla |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Edge Point Linking by Means of Global and Local Schemes |
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Book Chapter |
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Year |
2008 |
Publication |
in Signal Processing for Image Enhancement and Multimedia Processing |
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11 |
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115–125 |
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Springer |
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E. Damiani |
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ADAS |
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no |
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ADAS @ adas @ SaV2008 |
Serial |
938 |
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Author |
Misael Rosales; Petia Radeva; Oriol Rodriguez; Debora Gil |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Suppression of IVUS Image Rotation. A Kinematic Approach |
Type |
Book Chapter |
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Year |
2005 |
Publication |
Functional Imaging and Modeling of the Heart |
Abbreviated Journal |
LNCS |
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Volume |
3504 |
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Pages |
889-892 |
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IntraVascular Ultrasound (IVUS) is an exploratory technique used in interventional procedures that shows cross section images of arteries and provides qualitative information about the causes and severity of the arterial lumen narrowing. Cross section analysis as well as visualization of plaque extension in a vessel segment during the catheter imaging pullback are the technique main advantages. However, IVUS sequence exhibits a periodic rotation artifact that makes difficult the longitudinal lesion inspection and hinders any segmentation algorithm. In this paper we propose a new kinematic method to estimate and remove the image rotation of IVUS images sequences. Results on several IVUS sequences show good results and prompt some of the clinical applications to vessel dynamics study, and relation to vessel pathology. |
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Springer Berlin / Heidelberg |
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Frangi, Alejandro and Radeva, Petia and Santos, Andres and Hernandez, Monica |
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Lecture Notes in Computer Science |
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LNCS |
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3504 |
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IAM;MILAB |
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no |
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IAM @ iam @ RRR2005 |
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1645 |
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Author |
C. Alejandro Parraga |
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Title |
Perceptual Psychophysics |
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Book Chapter |
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2015 |
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Biologically-Inspired Computer Vision: Fundamentals and Applications |
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G.Cristobal; M.Keil; L.Perrinet |
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978-3-527-41264-8 |
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CIC; 600.074 |
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Admin @ si @ Par2015 |
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2600 |
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Author |
Antonio Lopez; Jiaolong Xu; Jose Luis Gomez; David Vazquez; German Ros |
![download PDF file pdf](img/file_PDF.gif)
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Title |
From Virtual to Real World Visual Perception using Domain Adaptation -- The DPM as Example |
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Book Chapter |
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Year |
2017 |
Publication |
Domain Adaptation in Computer Vision Applications |
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13 |
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243-258 |
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Domain Adaptation |
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Supervised learning tends to produce more accurate classifiers than unsupervised learning in general. This implies that training data is preferred with annotations. When addressing visual perception challenges, such as localizing certain object classes within an image, the learning of the involved classifiers turns out to be a practical bottleneck. The reason is that, at least, we have to frame object examples with bounding boxes in thousands of images. A priori, the more complex the model is regarding its number of parameters, the more annotated examples are required. This annotation task is performed by human oracles, which ends up in inaccuracies and errors in the annotations (aka ground truth) since the task is inherently very cumbersome and sometimes ambiguous. As an alternative we have pioneered the use of virtual worlds for collecting such annotations automatically and with high precision. However, since the models learned with virtual data must operate in the real world, we still need to perform domain adaptation (DA). In this chapter we revisit the DA of a deformable part-based model (DPM) as an exemplifying case of virtual- to-real-world DA. As a use case, we address the challenge of vehicle detection for driver assistance, using different publicly available virtual-world data. While doing so, we investigate questions such as: how does the domain gap behave due to virtual-vs-real data with respect to dominant object appearance per domain, as well as the role of photo-realism in the virtual world. |
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Springer |
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Editor ![sorted by Editor field, ascending order (up)](img/sort_asc.gif) |
Gabriela Csurka |
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ADAS; 600.085; 601.223; 600.076; 600.118 |
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no |
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ADAS @ adas @ LXG2017 |
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2872 |
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Author |
German Ros; Laura Sellart; Gabriel Villalonga; Elias Maidanik; Francisco Molero; Marc Garcia; Adriana Cedeño; Francisco Perez; Didier Ramirez; Eduardo Escobar; Jose Luis Gomez; David Vazquez; Antonio Lopez |
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Title |
Semantic Segmentation of Urban Scenes via Domain Adaptation of SYNTHIA |
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Book Chapter |
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Year |
2017 |
Publication |
Domain Adaptation in Computer Vision Applications |
Abbreviated Journal |
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Volume |
12 |
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Pages |
227-241 |
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SYNTHIA; Virtual worlds; Autonomous Driving |
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Abstract |
Vision-based semantic segmentation in urban scenarios is a key functionality for autonomous driving. Recent revolutionary results of deep convolutional neural networks (DCNNs) foreshadow the advent of reliable classifiers to perform such visual tasks. However, DCNNs require learning of many parameters from raw images; thus, having a sufficient amount of diverse images with class annotations is needed. These annotations are obtained via cumbersome, human labour which is particularly challenging for semantic segmentation since pixel-level annotations are required. In this chapter, we propose to use a combination of a virtual world to automatically generate realistic synthetic images with pixel-level annotations, and domain adaptation to transfer the models learnt to correctly operate in real scenarios. We address the question of how useful synthetic data can be for semantic segmentation – in particular, when using a DCNN paradigm. In order to answer this question we have generated a synthetic collection of diverse urban images, named SYNTHIA, with automatically generated class annotations and object identifiers. We use SYNTHIA in combination with publicly available real-world urban images with manually provided annotations. Then, we conduct experiments with DCNNs that show that combining SYNTHIA with simple domain adaptation techniques in the training stage significantly improves performance on semantic segmentation. |
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Springer |
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Editor ![sorted by Editor field, ascending order (up)](img/sort_asc.gif) |
Gabriela Csurka |
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ADAS; 600.085; 600.082; 600.076; 600.118 |
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no |
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ADAS @ adas @ RSV2017 |
Serial |
2882 |
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Permanent link to this record |
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Author |
V. Valev; Petia Radeva |
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Title |
Determining Structural Description by Boolean Formulas. |
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Book Chapter |
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Year |
1992 |
Publication |
Advances in Structural and Syntactic Pattern Recognition |
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5 |
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131–140 |
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Abstract |
Pattern recognition is an active area of research with many applications, some of which have reached commercial maturity. Structural and syntactic methods are very powerful. They are based on symbolic data structures together with matching, parsing, and reasoning procedures that are able to infer interpretations of complex input patterns.
This book gives an overview of the latest developments and achievements in the field. |
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World Scientific |
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Editor ![sorted by Editor field, ascending order (up)](img/sort_asc.gif) |
H. Bunke |
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Machine Perception and Artificial Intelligence: |
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978-981-279-791-9 |
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MILAB |
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no |
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BCNPCL @ bcnpcl @ VaR1992c |
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254 |
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Author |
Sergio Escalera; David M.J. Tax; Oriol Pujol; Petia Radeva; Robert P.W. Duin |
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Title |
Multi-Class Classification in Image Analysis Via Error-Correcting Output Codes |
Type |
Book Chapter |
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Year |
2011 |
Publication |
Innovations in Intelligent Image Analysis |
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Volume |
339 |
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Pages |
7-29 |
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A common way to model multi-class classification problems is by means of Error-Correcting Output Codes (ECOC). Given a multi-class problem, the ECOC technique designs a codeword for each class, where each position of the code identifies the membership of the class for a given binary problem.A classification decision is obtained by assigning the label of the class with the closest code. In this paper, we overview the state-of-the-art on ECOC designs and test them in real applications. Results on different multi-class data sets show the benefits of using the ensemble of classifiers when categorizing objects in images. |
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Springer Berlin Heidelberg |
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Berlin |
Editor ![sorted by Editor field, ascending order (up)](img/sort_asc.gif) |
H. Kawasnicka; L.Jain |
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1860-949X |
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978-3-642-17933-4 |
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MILAB;HuPBA |
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no |
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Admin @ si @ ETP2011 |
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1746 |
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Author |
Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru; Miguel Angel Gonzalez Ballester |
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Title |
Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs |
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Book Chapter |
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Year |
2012 |
Publication |
Workshop on Computational and Clinical Applications in Abdominal Imaging |
Abbreviated Journal |
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Volume |
7029 |
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Pages |
223–230 |
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medial manifolds, abdomen. |
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Abstract |
Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D
objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial
manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our
method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs,
exploring the use of medial manifolds for the representation of multi-organ relations. |
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Toronto; Canada; |
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Springer Link |
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Berlin |
Editor ![sorted by Editor field, ascending order (up)](img/sort_asc.gif) |
H. Yoshida et al |
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English |
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English |
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Lecture Notes in Computer Science |
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LNCS |
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0302-9743 |
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978-3-642-28556-1 |
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ABDI |
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Notes |
IAM;MV |
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no |
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Call Number |
IAM @ iam @ VGB2012 |
Serial |
1834 |
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Permanent link to this record |
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Author |
Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis |
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Title |
Prior Knowledge Based Motion Model Representation |
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Book Chapter |
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Year |
2009 |
Publication |
Progress in Computer Vision and Image Analysis |
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16 |
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Editor ![sorted by Editor field, ascending order (up)](img/sort_asc.gif) |
Horst Bunke; JuanJose Villanueva; Gemma Sanchez |
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ADAS |
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no |
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ADAS @ adas @ SAM2009 |
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1235 |
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Author |
Fernando Vilariño; Debora Gil; Petia Radeva |
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Title |
A Novel FLDA Formulation for Numerical Stability Analysis |
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Book Chapter |
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Year |
2004 |
Publication |
Recent Advances in Artificial Intelligence Research and Development |
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113 |
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77-84 |
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Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision |
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Abstract |
Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision. |
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IOS Press |
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Editor ![sorted by Editor field, ascending order (up)](img/sort_asc.gif) |
J. Vitrià, P. Radeva and I. Aguiló |
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978-1-58603-466-5 |
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MV;IAM;MILAB;SIAI |
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IAM @ iam @ VGR2004 |
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1663 |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva |
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Title |
A Machine Learning framework using SOMs: Applications in the Intestinal Motility Assessment |
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Book Chapter |
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Year |
2006 |
Publication |
11th Iberoamerican Congress on Pattern Recognition |
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4225 |
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188–197 |
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Small Bowel Motility Assessment by means of Wireless Capsule Video Endoscopy constitutes a novel clinical methodology in which a capsule with a micro-camera attached to it is swallowed by the patient, emitting a RF signal which is recorded as a video of its trip throughout the gut. In order to overcome the main drawbacks associated with this technique -mainly related to the large amount of visualization time required-, our efforts have been focused on the development of a machine learning system, built up in sequential stages, which provides the specialists with the useful part of the video, rejecting those parts not valid for analysis. We successfully used Self Organized Maps in a general semi-supervised framework with the aim of tackling the different learning stages of our system. The analysis of the diverse types of images and the automatic detection of intestinal contractions is performed under the perspective of intestinal motility assessment in a clinical environment. |
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Cancun (Mexico) |
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Springer Verlag |
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Berlin-Heidelberg |
Editor ![sorted by Editor field, ascending order (up)](img/sort_asc.gif) |
J.P. Martinez–Trinidad et al |
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LNCS |
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800 |
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CIARP06 |
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MV;OR;MILAB;SIAI |
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no |
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BCNPCL @ bcnpcl @ VSV2006d; IAM @ iam @ VSV2006e |
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729 |
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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 |
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Book Chapter |
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2020 |
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Visual Text Interpretation – Algorithms and Applications in Scene Understanding and Document Analysis |
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Springer |
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Editor ![sorted by Editor field, ascending order (up)](img/sort_asc.gif) |
K. Alahari; C.V. Jawahar |
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Series on Advances in Computer Vision and Pattern Recognition |
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DAG; 600.121 |
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no |
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GNR2020 |
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3494 |
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Author |
Lluis Gomez; Dena Bazazian; Dimosthenis Karatzas |
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Title |
Historical review of scene text detection research |
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Book Chapter |
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2020 |
Publication |
Visual Text Interpretation – Algorithms and Applications in Scene Understanding and Document Analysis |
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Springer |
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Editor ![sorted by Editor field, ascending order (up)](img/sort_asc.gif) |
K. Alahari; C.V. Jawahar |
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Series on Advances in Computer Vision and Pattern Recognition |
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DAG; 600.121 |
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Call Number |
Admin @ si @ GBK2020 |
Serial |
3495 |
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Author |
Joana Maria Pujadas-Mora; Alicia Fornes; Josep Llados; Anna Cabre |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Bridging the gap between historical demography and computing: tools for computer-assisted transcription and the analysis of demographic sources |
Type |
Book Chapter |
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Year |
2016 |
Publication |
The future of historical demography. Upside down and inside out |
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127-131 |
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Acco Publishers |
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K.Matthijs; S.Hin; H.Matsuo; J.Kok |
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978-94-6292-722-3 |
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DAG; 600.097 |
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no |
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Admin @ si @ PFL2016 |
Serial |
2907 |
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Author |
Xavier Baro; Jordi Vitria |
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Title |
Evolutionary Object Detection by Means of Naive Bayes Models Estimation |
Type |
Book Chapter |
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Year |
2008 |
Publication |
Applications of Evolutionary Computing. EvoWorkshops |
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Volume |
4974 |
Issue |
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Pages |
235–244 |
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Address |
Naples (Italy) |
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M. Giacobini |
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Notes |
OR;HuPBA;MV |
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no |
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Call Number |
BCNPCL @ bcnpcl @ BaV2008a |
Serial |
976 |
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Permanent link to this record |