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Author O. Rodriguez; J. Mauri; E Fernandez-Nofrerias; C. Garcia; R. Villuendas; A. Tovar; A. Duran; V. Valle; Misael Rosales; Petia Radeva edit  openurl
  Title Model Empiric de Simulacio d Ecografia Intravascular Type Journal Article
  Year 2003 Publication Revista Societat Catalana de Cardiologia, 4(4):42, XIVe Congres de la Societat Catalana de Cardiologia Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Barcelona  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area (down) Expedition Conference  
  Notes MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ RMF2003e Serial 412  
Permanent link to this record
 
 
Author A.F. Sole; Antonio Lopez; G. Sapiro edit   pdf
openurl 
  Title Crease Enhancement Diffusion Type Journal Article
  Year 2001 Publication Computer Vision and Image Understanding, 84(2): 241–248 (IF: 1.298) Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address New York; USA  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
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  ISSN ISBN Medium  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ SLS2001 Serial 485  
Permanent link to this record
 
 
Author Debora Gil; Petia Radeva edit   pdf
doi  openurl
  Title A Regularized Curvature Flow Designed for a Selective Shape Restoration Type Journal Article
  Year 2004 Publication IEEE Transactions on Image Processing Abbreviated Journal  
  Volume 13 Issue Pages 1444–1458  
  Keywords Geometric flows, nonlinear filtering, shape recovery.  
  Abstract Among all filtering techniques, those based exclu- sively on image level sets (geometric flows) have proven to be the less sensitive to the nature of noise and the most contrast preserving. A common feature to existent curvature flows is that they penalize high curvature, regardless of the curve regularity. This constitutes a major drawback since curvature extreme values are standard descriptors of the contour geometry. We argue that an operator designed with shape recovery purposes should include a term penalizing irregularity in the curvature rather than its magnitude. To this purpose, we present a novel geometric flow that includes a function that measures the degree of local irregularity present in the curve. A main advantage is that it achieves non-trivial steady states representing a smooth model of level curves in a noisy image. Performance of our approach is compared to classical filtering techniques in terms of quality in the restored image/shape and asymptotic behavior. We empirically prove that our approach is the technique that achieves the best compromise between image quality and evolution stabilization.  
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  Notes IAM;MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ GiR2004b Serial 491  
Permanent link to this record
 
 
Author Maria Vanrell; Jordi Vitria edit  doi
openurl 
  Title Optimal 3x3 decomposable disks for morphological transformations Type Journal Article
  Year 1997 Publication Image and Vision Computing Abbreviated Journal  
  Volume 15 Issue 11 Pages 845-854  
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  Notes OR;CIC;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ VaV1997c Serial 543  
Permanent link to this record
 
 
Author Antonio Lopez; Ernest Valveny; Juan J. Villanueva edit  url
openurl 
  Title Real-time quality control of surgical material packaging by artificial vision Type Journal Article
  Year 2005 Publication Assembly Automation Abbreviated Journal  
  Volume 25 Issue 3 Pages  
  Keywords  
  Abstract IF: 0.061)  
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  Notes ADAS;DAG Approved no  
  Call Number ADAS @ adas @ LVV2005 Serial 552  
Permanent link to this record
 
 
Author A. Sanfeliu; Juan J. Villanueva edit  url
doi  openurl
  Title An approach of visual motion analysis Type Journal Article
  Year 2005 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 26 Issue 3 Pages 355–368  
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  Abstract IF: 1.138  
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  Notes Approved no  
  Call Number ISE @ ise @ SaV2005 Serial 561  
Permanent link to this record
 
 
Author Jaume Amores; Petia Radeva edit  url
doi  openurl
  Title Registration and Retrieval of Highly Elastic Bodies using Contextual Information Type Journal Article
  Year 2005 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 26 Issue 11 Pages 1720–1731  
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  Abstract IF: 1.138  
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  Notes ADAS;MILAB Approved no  
  Call Number ADAS @ adas @ AmR2005b Serial 592  
Permanent link to this record
 
 
Author B. Gotschy; Matthias S. Keil; H. Klos; I. Rystau edit  doi
openurl 
  Title Transition from static to dynamic Jahn-Teller distortion in (P(C6 H5)4)2 C60| Type Journal Article
  Year 1994 Publication Solid State Communications Abbreviated Journal  
  Volume 92 Issue 12 Pages 935-938  
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  Notes Approved no  
  Call Number Admin @ si @ GKK1994 Serial 631  
Permanent link to this record
 
 
Author Oriol Ramos Terrades; Ernest Valveny edit  doi
openurl 
  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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  Notes DAG Approved no  
  Call Number DAG @ dag @ RaV2006a Serial 635  
Permanent link to this record
 
 
Author Jaume Amores; N. Sebe; Petia Radeva edit  doi
openurl 
  Title Boosting the distance estimation: Application to the K-Nearest Neighbor Classifier Type Journal Article
  Year 2006 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 27 Issue 3 Pages 201–209  
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  Notes ADAS;MILAB Approved no  
  Call Number ADAS @ adas @ ASR2006 Serial 643  
Permanent link to this record
 
 
Author Angel Sappa; David Geronimo; Fadi Dornaika; Antonio Lopez edit   pdf
url  openurl
  Title On-board camera extrinsic parameter estimation Type Journal Article
  Year 2006 Publication Electronics Letters Abbreviated Journal EL  
  Volume 42 Issue 13 Pages 745–746  
  Keywords  
  Abstract An efficient technique for real-time estimation of camera extrinsic parameters is presented. It is intended to be used on on-board vision systems for driving assistance applications. The proposed technique is based on the use of a commercial stereo vision system that does not need any visual feature extraction.  
  Address  
  Corporate Author Thesis  
  Publisher IEE Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area (down) Expedition Conference  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ SGD2006a Serial 655  
Permanent link to this record
 
 
Author Xavier Otazu; Oriol Pujol edit  doi
openurl 
  Title Wavelet based approach to cluster analysis. Application on low dimensional data sets Type Journal Article
  Year 2006 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 27 Issue 14 Pages 1590–1605  
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  Notes MILAB; CIC; HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ OtP2006 Serial 658  
Permanent link to this record
 
 
Author Jaume Amores edit   pdf
doi  openurl
  Title Multiple Instance Classification: review, taxonomy and comparative study Type Journal Article
  Year 2013 Publication Artificial Intelligence Abbreviated Journal AI  
  Volume 201 Issue Pages 81-105  
  Keywords Multi-instance learning; Codebook; Bag-of-Words  
  Abstract Multiple Instance Learning (MIL) has become an important topic in the pattern recognition community, and many solutions to this problemhave been proposed until now. Despite this fact, there is a lack of comparative studies that shed light into the characteristics and behavior of the different methods. In this work we provide such an analysis focused on the classification task (i.e.,leaving out other learning tasks such as regression). In order to perform our study, we implemented
fourteen methods grouped into three different families. We analyze the performance of the approaches across a variety of well-known databases, and we also study their behavior in synthetic scenarios in order to highlight their characteristics. As a result of this analysis, we conclude that methods that extract global bag-level information show a clearly superior performance in general. In this sense, the analysis permits us to understand why some types of methods are more successful than others, and it permits us to establish guidelines in the design of new MIL
methods.		  
  Address  
  Corporate Author Thesis  
  Publisher Elsevier Science Publishers Ltd. Essex, UK Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0004-3702 ISBN Medium  
  Area (down) Expedition Conference  
  Notes ADAS; 601.042; 600.057 Approved no  
  Call Number Admin @ si @ Amo2013 Serial 2273  
Permanent link to this record
 
 
Author Jaume Amores edit   pdf
doi  openurl
  Title MILDE: multiple instance learning by discriminative embedding Type Journal Article
  Year 2015 Publication Knowledge and Information Systems Abbreviated Journal KAIS  
  Volume 42 Issue 2 Pages 381-407  
  Keywords Multi-instance learning; Codebook; Bag of words  
  Abstract While the objective of the standard supervised learning problem is to classify feature vectors, in the multiple instance learning problem, the objective is to classify bags, where each bag contains multiple feature vectors. This represents a generalization of the standard problem, and this generalization becomes necessary in many real applications such as drug activity prediction, content-based image retrieval, and others. While the existing paradigms are based on learning the discriminant information either at the instance level or at the bag level, we propose to incorporate both levels of information. This is done by defining a discriminative embedding of the original space based on the responses of cluster-adapted instance classifiers. Results clearly show the advantage of the proposed method over the state of the art, where we tested the performance through a variety of well-known databases that come from real problems, and we also included an analysis of the performance using synthetically generated data.  
  Address  
  Corporate Author Thesis  
  Publisher Springer London Place of Publication Editor  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0219-1377 ISBN Medium  
  Area (down) Expedition Conference  
  Notes ADAS; 601.042; 600.057; 600.076 Approved no  
  Call Number Admin @ si @ Amo2015 Serial 2383  
Permanent link to this record
 
 
Author Albert Gordo; Florent Perronnin; Yunchao Gong; Svetlana Lazebnik edit   pdf
doi  openurl
  Title Asymmetric Distances for Binary Embeddings Type Journal Article
  Year 2014 Publication IEEE Transactions on Pattern Analysis and Machine Intelligence Abbreviated Journal TPAMI  
  Volume 36 Issue 1 Pages 33-47  
  Keywords  
  Abstract In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes which binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances which are applicable to a wide variety of embedding techniques including Locality Sensitive Hashing (LSH), Locality Sensitive Binary Codes (LSBC), Spectral Hashing (SH), PCA Embedding (PCAE), PCA Embedding with random rotations (PCAE-RR), and PCA Embedding with iterative quantization (PCAE-ITQ). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques.  
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  Series Volume Series Issue Edition  
  ISSN 0162-8828 ISBN Medium  
  Area (down) Expedition Conference  
  Notes DAG; 600.045; 605.203; 600.077 Approved no  
  Call Number Admin @ si @ GPG2014 Serial 2272  
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