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Author David Guillamet; Jordi Vitria; B. Shiele
Title Introducing a weighted non-negative matrix factorization for image classification Type Journal Article
Year 2003 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 24 Issue 14 Pages 2447–2454
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Abstract IF: 0.809
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Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ GVS2003 Serial 382
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Author Judit Martinez; Eva Costa; P. Herreros; F. Javier Sanchez; Ramon Baldrich
Title A Modular and Scalable Architecture for PC-Based Real-Time Vision Systems Type Journal Article
Year 2003 Publication Real–Time Imaging, (IF: 0.512) Abbreviated Journal
Volume 9 Issue Pages 99-112
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Notes CIC Approved no
Call Number CAT @ cat @ MCH2003b Serial 394
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Author Daniel Ponsa; Robert Benavente; Felipe Lumbreras; Judit Martinez; Xavier Roca
Title Quality control of safety belts by machine vision inspection for real-time production Type Journal Article
Year 2003 Publication Optical Engineering (IF: 0.877) Abbreviated Journal
Volume 42 Issue 4 Pages 1114-1120
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Publisher SPIE Place of Publication Editor
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Notes ADAS;ISE;CIC Approved no
Call Number ADAS @ adas @ PRL2003 Serial 399
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Author Debora Gil; Petia Radeva
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
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Author Antonio Lopez; Ernest Valveny; Juan J. Villanueva
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
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Abstract IF: 0.061)
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Notes ADAS;DAG Approved no
Call Number ADAS @ adas @ LVV2005 Serial 552
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Author A. Sanfeliu; Juan J. Villanueva
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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Publisher Place of Publication Editor
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Notes Approved no
Call Number ISE @ ise @ SaV2005 Serial 561
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Author Jaume Amores; Petia Radeva
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
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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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Notes DAG Approved no
Call Number DAG @ dag @ RaV2006a Serial 635
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Author Jaume Amores; N. Sebe; Petia Radeva
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
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Author Fernando Vilariño; Ludmila I. Kuncheva; Petia Radeva
Title ROC curves and video analysis optimization in intestinal capsule endoscopy Type Journal Article
Year 2006 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 27 Issue 8 Pages 875–881
Keywords ROC curves; Classification; Classifiers ensemble; Detection of intestinal contractions; Imbalanced classes; Wireless capsule endoscopy
Abstract Wireless capsule endoscopy involves inspection of hours of video material by a highly qualified professional. Time episodes corresponding to intestinal contractions, which are of interest to the physician constitute about 1% of the video. The problem is to label automatically time episodes containing contractions so that only a fraction of the video needs inspection. As the classes of contraction and non-contraction images in the video are largely imbalanced, ROC curves are used to optimize the trade-off between false positive and false negative rates. Classifier ensemble methods and simple classifiers were examined. Our results reinforce the claims from recent literature that classifier ensemble methods specifically designed for imbalanced problems have substantial advantages over simple classifiers and standard classifier ensembles. By using ROC curves with the bagging ensemble method the inspection time can be drastically reduced at the expense of a small fraction of missed contractions.
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Area 800 Expedition Conference
Notes MILAB;MV;SIAI Approved no
Call Number BCNPCL @ bcnpcl @ VKR2006; IAM @ iam @ VKR2006 Serial 647
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Author Angel Sappa; David Geronimo; Fadi Dornaika; Antonio Lopez
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
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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.
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Publisher IEE Place of Publication Editor
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Notes ADAS Approved no
Call Number ADAS @ adas @ SGD2006a Serial 655
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Author Xavier Otazu; Oriol Pujol
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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Abstract
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Notes MILAB; CIC; HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ OtP2006 Serial 658
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Author Jaume Amores
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.
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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 Expedition Conference
Notes ADAS; 601.042; 600.057 Approved no
Call Number Admin @ si @ Amo2013 Serial 2273
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Author Jaume Amores
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.
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Publisher Springer London Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0219-1377 ISBN Medium
Area Expedition Conference
Notes ADAS; 601.042; 600.057; 600.076 Approved no
Call Number Admin @ si @ Amo2015 Serial 2383
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Author Albert Gordo; Florent Perronnin; Yunchao Gong; Svetlana Lazebnik
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
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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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ISSN 0162-8828 ISBN Medium
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Notes DAG; 600.045; 605.203; 600.077 Approved no
Call Number Admin @ si @ GPG2014 Serial 2272
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