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Author |
Jaume Garcia; Joel Barajas; Francesc Carreras; Sandra Pujades; Petia Radeva |
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Title |
An intuitive validation technique to compare local versus global tagged MRI analysis |
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Conference Article |
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Year |
2005 |
Publication |
Computers In Cardiology |
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Volume |
32 |
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29–32 |
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Myocardium appears as a uniform tissue that seen in convectional Magnetic Resonance Images (MRI) shows just the contractile part of its movement. MR Tagging is a unique imaging technique that prints a grid over the tissue which moves according to the underlying movement of the myocardium revealing the true deformation of the cardiac muscle. Optical flow techniques based on spectral information estimate tissue displacement by analyzing information encoded in the phase maps which can be obtained using, local (Gabor) and global (HARP) methods. In this paper we compare both in synthetic and real Tagged MR sequences. We conclude that local method is slightly more accurate than the global one. On the other hand, global method is more efficient as it is much faster and less parameters have to be taken into account |
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Lyon (France) |
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0-7803-9337-6 |
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IAM;MILAB |
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IAM @ iam @ GBC2005 |
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639 |
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Author |
Ferran Poveda; Jaume Garcia; Enric Marti; Debora Gil |
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Title |
Validation of the myocardial architecture in DT-MRI tractography |
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Conference Article |
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Year |
2010 |
Publication |
Medical Image Computing in Catalunya: Graduate Student Workshop |
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29-30 |
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Deep understanding of myocardial structure may help to link form and funcion of the heart unraveling crucial knowledge for medical and surgical clinical procedures and studies. In this work we introduce two visualization techniques based on DT-MRI streamlining able to decipher interesting properties of the architectural organization of the heart. |
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Girona (Spain) |
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MICCAT |
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IAM |
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IAM @ iam @ PGM2010 |
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1626 |
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Author |
Andreas Fischer; Volkmar Frinken; Alicia Fornes; Horst Bunke |
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Title |
Transcription Alignment of Latin Manuscripts Using Hidden Markov Models |
Type |
Conference Article |
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Year |
2011 |
Publication |
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing |
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29-36 |
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Transcriptions of historical documents are a valuable source for extracting labeled handwriting images that can be used for training recognition systems. In this paper, we introduce the Saint Gall database that includes images as well as the transcription of a Latin manuscript from the 9th century written in Carolingian script. Although the available transcription is of high quality for a human reader, the spelling of the words is not accurate when compared with the handwriting image. Hence, the transcription poses several challenges for alignment regarding, e.g., line breaks, abbreviations, and capitalization. We propose an alignment system based on character Hidden Markov Models that can cope with these challenges and efficiently aligns complete document pages. On the Saint Gall database, we demonstrate that a considerable alignment accuracy can be achieved, even with weakly trained character models. |
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ACM |
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HIP |
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DAG |
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Admin @ si @ FFF2011b |
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1824 |
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Author |
Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera |
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Title |
Three-Dimensional Design of Error Correcting Output Codes |
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Conference Article |
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2012 |
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8th International Conference on Machine Learning and Data Mining |
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29- |
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Berlin, Germany |
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MLDM |
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HuPBA;MILAB |
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Admin @ si @ BGE2012a |
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2041 |
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Author |
Quentin Angermann; Jorge Bernal; Cristina Sanchez Montes; Gloria Fernandez Esparrach; Xavier Gray; Olivier Romain; F. Javier Sanchez; Aymeric Histace |
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Title |
Towards Real-Time Polyp Detection in Colonoscopy Videos: Adapting Still Frame-Based Methodologies for Video Sequences Analysis |
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Conference Article |
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2017 |
Publication |
4th International Workshop on Computer Assisted and Robotic Endoscopy |
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29-41 |
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Polyp detection; colonoscopy; real time; spatio temporal coherence |
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Abstract |
Colorectal cancer is the second cause of cancer death in United States: precursor lesions (polyps) detection is key for patient survival. Though colonoscopy is the gold standard screening tool, some polyps are still missed. Several computational systems have been proposed but none of them are used in the clinical room mainly due to computational constraints. Besides, most of them are built over still frame databases, decreasing their performance on video analysis due to the lack of output stability and not coping with associated variability on image quality and polyp appearance. We propose a strategy to adapt these methods to video analysis by adding a spatio-temporal stability module and studying a combination of features to capture polyp appearance variability. We validate our strategy, incorporated on a real-time detection method, on a public video database. Resulting method detects all
polyps under real time constraints, increasing its performance due to our
adaptation strategy. |
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Quebec; Canada; September 2017 |
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CARE |
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MV; 600.096; 600.075 |
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no |
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Admin @ si @ ABS2017b |
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2977 |
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Author |
Pau Riba; Anjan Dutta; Josep Llados; Alicia Fornes |
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Title |
Graph-based deep learning for graphics classification |
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Conference Article |
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Year |
2017 |
Publication |
14th International Conference on Document Analysis and Recognition |
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29-30 |
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Graph-based representations are a common way to deal with graphics recognition problems. However, previous works were mainly focused on developing learning-free techniques. The success of deep learning frameworks have proved that learning is a powerful tool to solve many problems, however it is not straightforward to extend these methodologies to non euclidean data such as graphs. On the other hand, graphs are a good representational structure for graphical entities. In this work, we present some deep learning techniques that have been proposed in the literature for graph-based representations and
we show how they can be used in graphics recognition problems |
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DAG; 600.097; 601.302; 600.121 |
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no |
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Admin @ si @ RDL2017b |
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3058 |
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Author |
Joana Maria Pujadas-Mora; Alicia Fornes; Josep Llados; Gabriel Brea-Martinez; Miquel Valls-Figols |
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Title |
The Baix Llobregat (BALL) Demographic Database, between Historical Demography and Computer Vision (nineteenth–twentieth centuries |
Type |
Book Chapter |
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Year |
2019 |
Publication |
Nominative Data in Demographic Research in the East and the West: monograph |
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29-61 |
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Abstract |
The Baix Llobregat (BALL) Demographic Database is an ongoing database project containing individual census data from the Catalan region of Baix Llobregat (Spain) during the nineteenth and twentieth centuries. The BALL Database is built within the project ‘NETWORKS: Technology and citizen innovation for building historical social networks to understand the demographic past’ directed by Alícia Fornés from the Center for Computer Vision and Joana Maria Pujadas-Mora from the Center for Demographic Studies, both at the Universitat Autònoma de Barcelona, funded by the Recercaixa program (2017–2019).
Its webpage is http://dag.cvc.uab.es/xarxes/.The aim of the project is to develop technologies facilitating massive digitalization of demographic sources, and more specifically the padrones (local censuses), in order to reconstruct historical ‘social’ networks employing computer vision technology. Such virtual networks can be created thanks to the linkage of nominative records compiled in the local censuses across time and space. Thus, digitized versions of individual and family lifespans are established, and individuals and families can be located spatially. |
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978-5-7996-2656-3 |
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Notes |
DAG; 600.121 |
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no |
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Call Number |
Admin @ si @ PFL2019 |
Serial |
3351 |
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Author |
Manuel Carbonell; Joan Mas; Mauricio Villegas; Alicia Fornes; Josep Llados |
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Title |
End-to-End Handwritten Text Detection and Transcription in Full Pages |
Type |
Conference Article |
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Year |
2019 |
Publication |
2nd International Workshop on Machine Learning |
Abbreviated Journal |
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5 |
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29-34 |
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Handwritten Text Recognition; Layout Analysis; Text segmentation; Deep Neural Networks; Multi-task learning |
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When transcribing handwritten document images, inaccuracies in the text segmentation step often cause errors in the subsequent transcription step. For this reason, some recent methods propose to perform the recognition at paragraph level. But still, errors in the segmentation of paragraphs can affect
the transcription performance. In this work, we propose an end-to-end framework to transcribe full pages. The joint text detection and transcription allows to remove the layout analysis requirement at test time. The experimental results show that our approach can achieve comparable results to models that assume
segmented paragraphs, and suggest that joining the two tasks brings an improvement over doing the two tasks separately. |
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Sydney; Australia; September 2019 |
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DAG; 600.140; 601.311; 600.140 |
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no |
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Admin @ si @ CMV2019 |
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3353 |
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Author |
Partha Pratim Roy; Josep Llados |
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Title |
Multi-Oriented Character Recognition from Graphical Documents |
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Conference Article |
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2008 |
Publication |
2nd International Conference on Cognition and Recognition |
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30–35 |
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Mandya (India) |
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ICCR |
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DAG |
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DAG @ dag @ RLP2008 |
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965 |
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Author |
Alicia Fornes; Sergio Escalera; Josep Llados; Gemma Sanchez; Joan Mas |
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Title |
Hand Drawn Symbol Recognition by Blurred Shape Model Descriptor and a Multiclass Classifier |
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Book Chapter |
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2008 |
Publication |
Graphics Recognition: Recent Advances and New Opportunities |
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5046 |
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30–40 |
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W. Liu, J. Llados, J.M. Ogier |
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DAG; HUPBA; MILAB |
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no |
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BCNPCL @ bcnpcl @ FEL2008 |
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989 |
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Author |
Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
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Title |
Toward the Detection of Urban Infrastructures Edge Shadows |
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Conference Article |
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2010 |
Publication |
12th International Conference on Advanced Concepts for Intelligent Vision Systems |
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6474 |
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I |
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30–37 |
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In this paper, we propose a novel technique to detect the shadows cast by urban infrastructure, such as buildings, billboards, and traffic signs, using a sequence of images taken from a fixed camera. In our approach, we compute two different background models in parallel: one for the edges and one for the reflected light intensity. An algorithm is proposed to train the system to distinguish between moving edges in general and edges that belong to static objects, creating an edge background model. Then, during operation, a background intensity model allow us to separate between moving and static objects. Those edges included in the moving objects and those that belong to the edge background model are subtracted from the current image edges. The remaining edges are the ones cast by urban infrastructure. Our method is tested on a typical crossroad scene and the results show that the approach is sound and promising. |
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Sydney, Australia |
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Springer Berlin Heidelberg |
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eds. Blanc–Talon et al |
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0302-9743 |
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978-3-642-17687-6 |
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ACIVS |
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OR;MV |
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no |
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BCNPCL @ bcnpcl @ ISR2010 |
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1458 |
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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
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Title |
Graph of Words Embedding for Molecular Structure-Activity Relationship Analysis |
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Conference Article |
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2010 |
Publication |
15th Iberoamerican Congress on Pattern Recognition |
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6419 |
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30–37 |
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Structure-Activity relationship analysis aims at discovering chemical activity of molecular compounds based on their structure. In this article we make use of a particular graph representation of molecules and propose a new graph embedding procedure to solve the problem of structure-activity relationship analysis. The embedding is essentially an arrangement of a molecule in the form of a vector by considering frequencies of appearing atoms and frequencies of covalent bonds between them. Results on two benchmark databases show the effectiveness of the proposed technique in terms of recognition accuracy while avoiding high operational costs in the transformation. |
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Sao Paulo, Brazil |
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0302-9743 |
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978-3-642-16686-0 |
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CIARP |
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DAG |
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DAG @ dag @ GVB2010 |
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1462 |
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Author |
Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez |
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Title |
On-line lumen centre detection in gastrointestinal and respiratory endoscopy |
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Conference Article |
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Year |
2013 |
Publication |
Second International Workshop Clinical Image-Based Procedures |
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8361 |
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31-38 |
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Lumen centre detection; Bronchoscopy; Colonoscopy |
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We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %). |
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Nagoya; Japan; September 2013 |
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Springer International Publishing |
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Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus |
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978-3-319-05665-4 |
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800 |
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CLIP |
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MV; IAM; 600.047; 600.044; 600.060 |
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Admin @ si @ SBG2013 |
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2302 |
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Author |
Joost Van de Weijer; Fahad Shahbaz Khan; Marc Masana |
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Title |
Interactive Visual and Semantic Image Retrieval |
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Book Chapter |
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2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
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48 |
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31-35 |
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One direct consequence of recent advances in digital visual data generation and the direct availability of this information through the World-Wide Web, is a urgent demand for efficient image retrieval systems. The objective of image retrieval is to allow users to efficiently browse through this abundance of images. Due to the non-expert nature of the majority of the internet users, such systems should be user friendly, and therefore avoid complex user interfaces. In this chapter we investigate how high-level information provided by recently developed object recognition techniques can improve interactive image retrieval. Wel apply a bagof- word based image representation method to automatically classify images in a number of categories. These additional labels are then applied to improve the image retrieval system. Next to these high-level semantic labels, we also apply a low-level image description to describe the composition and color scheme of the scene. Both descriptions are incorporated in a user feedback image retrieval setting. The main objective is to show that automatic labeling of images with semantic labels can improve image retrieval results. |
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Springer Berlin Heidelberg |
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Angel Sappa; Jordi Vitria |
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1868-4394 |
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978-3-642-35931-6 |
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CIC; 605.203; 600.048 |
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Admin @ si @ WKC2013 |
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2284 |
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Author |
Sounak Dey; Anjan Dutta; Josep Llados; Alicia Fornes; Umapada Pal |
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Shallow Neural Network Model for Hand-drawn Symbol Recognition in Multi-Writer Scenario |
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2017 |
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14th International Conference on Document Analysis and Recognition |
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31-32 |
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One of the main challenges in hand drawn symbol recognition is the variability among symbols because of the different writer styles. In this paper, we present and discuss some results recognizing hand-drawn symbols with a shallow neural network. A neural network model inspired from the LeNet architecture has been used to achieve state-of-the-art results with
very less training data, which is very unlikely to the data hungry deep neural network. From the results, it has become evident that the neural network architectures can efficiently describe and recognize hand drawn symbols from different writers and can model the inter author aberration |
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DAG; 600.097; 600.121 |
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Admin @ si @ DDL2017 |
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3057 |
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