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Author Debora Gil; Petia Radeva; Fernando Vilariño edit   pdf
doi  isbn
openurl 
  Title (up) Anisotropic Contour Completion Type Conference Article
  Year 2003 Publication Proceedings of the IEEE International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages I-869  
  Keywords  
  Abstract In this paper we introduce a novel application of the diffusion tensor for anisotropic image processing. The Anisotropic Contour Completion (ACC) we suggest consists in extending the characteristic function of the open curve by means of a degenerated diffusion tensor that prevents any diffusion in the normal direction. We show that ACC is equivalent to a dilation with a continuous elliptic structural element that takes into account the local orientation of the contours to be closed. Experiments on contours extracted from real images show that ACC produces shapes able to adapt to any curve in an active contour framework. 1.  
  Address Barcelona, Spain  
  Corporate Author Thesis  
  Publisher Place of Publication Barcelona, Spain Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 0-7803-7751-6 Medium  
  Area Expedition Conference ICIP  
  Notes IAM;MV;MILAB;SIAI Approved no  
  Call Number IAM @ iam @ GRV2003 Serial 1539  
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Author Aura Hernandez-Sabate; Debora Gil; Petia Radeva; E.N.Nofrerias edit   pdf
doi  openurl
  Title (up) Anisotropic processing of image structures for adventitia detection in intravascular ultrasound images Type Conference Article
  Year 2004 Publication Proc. Computers in Cardiology Abbreviated Journal  
  Volume 31 Issue Pages 229-232  
  Keywords  
  Abstract The adventitia layer appears as a weak edge in IVUS images with a non-uniform grey level, which difficulties its detection. In order to enhance edges, we apply an anisotropic filter that homogenizes the grey level along the image significant structures (ridges, valleys and edges). A standard edge detector applied to the filtered image yields a set of candidate points prone to be unconnected. The final model is obtained by interpolating the former line segments along the tangent direction to the level curves of the filtered image with an anisotropic contour closing technique based on functional extension principles  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Chicago (USA) Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM; MILAB Approved no  
  Call Number IAM @ iam @ HGR2004 Serial 1555  
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Author Joan Serrat edit  openurl
  Title (up) Aplicacion del analisis de imagenes en radiologia. Type Conference Article
  Year 1995 Publication VI National Simposium on Pattern Recognition and image Analysis Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  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 Expedition Conference IbPRIA  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ Ser1995 Serial 120  
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Author Eirikur Agustsson; Radu Timofte; Sergio Escalera; Xavier Baro; Isabelle Guyon; Rasmus Rothe edit   pdf
doi  openurl
  Title (up) Apparent and real age estimation in still images with deep residual regressors on APPA-REAL database Type Conference Article
  Year 2017 Publication 12th IEEE International Conference on Automatic Face and Gesture Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract After decades of research, the real (biological) age estimation from a single face image reached maturity thanks to the availability of large public face databases and impressive accuracies achieved by recently proposed methods.
The estimation of “apparent age” is a related task concerning the age perceived by human observers. Significant advances have been also made in this new research direction with the recent Looking At People challenges. In this paper we make several contributions to age estimation research. (i) We introduce APPA-REAL, a large face image database with both real and apparent age annotations. (ii) We study the relationship between real and apparent age. (iii) We develop a residual age regression method to further improve the performance. (iv) We show that real age estimation can be successfully tackled as an apparent age estimation followed by an apparent to real age residual regression. (v) We graphically reveal the facial regions on which the CNN focuses in order to perform apparent and real age estimation tasks.
 
  Address Washington;USA; May 2017  
  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 Expedition Conference FG  
  Notes HUPBA; no menciona Approved no  
  Call Number Admin @ si @ ATE2017 Serial 3013  
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Author Bogdan Raducanu; Fadi Dornaika edit   pdf
doi  isbn
openurl 
  Title (up) Appearance-based Face Recognition Using A Supervised Manifold Learning Framework Type Conference Article
  Year 2012 Publication IEEE Workshop on the Applications of Computer Vision Abbreviated Journal  
  Volume Issue Pages 465-470  
  Keywords  
  Abstract Many natural image sets, depicting objects whose appearance is changing due to motion, pose or light variations, can be considered samples of a low-dimension nonlinear manifold embedded in the high-dimensional observation space (the space of all possible images). The main contribution of our work is represented by a Supervised Laplacian Eigemaps (S-LE) algorithm, which exploits the class label information for mapping the original data in the embedded space. Our proposed approach benefits from two important properties: i) it is discriminative, and ii) it adaptively selects the neighbors of a sample without using any predefined neighborhood size. Experiments were conducted on four face databases and the results demonstrate that the proposed algorithm significantly outperforms many linear and non-linear embedding techniques. Although we've focused on the face recognition problem, the proposed approach could also be extended to other category of objects characterized by large variance in their appearance.  
  Address Breckenridge; CO; USA  
  Corporate Author Thesis  
  Publisher IEEE Xplore Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1550-5790 ISBN 978-1-4673-0233-3 Medium  
  Area Expedition Conference WACV  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ RaD2012d Serial 1890  
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Author Ernest Valveny; Enric Marti edit   pdf
url  doi
openurl 
  Title (up) Application of deformable template matching to symbol recognition in hand-written architectural draw Type Conference Article
  Year 1999 Publication Proceedings of the Fifth International Conference on Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract We propose to use deformable template matching as a new approach to recognize characters and lineal symbols in hand-written line drawings, instead of traditional methods based on vectorization and feature extraction. Bayesian formulation of the deformable template matching allows combining fidelity to the ideal shape of the symbol with maximum flexibility to get the best fit to the input image. Lineal nature of symbols can be exploited to define a suitable representation of models and the set of deformations to be applied to them. Matching, however, is done over the original binary image to avoid losing relevant features during vectorization. We have applied this method to hand-written architectural drawings and experimental results demonstrate that symbols with high distortions from ideal shape can be accurately identified.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Bangalore (India) Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ VAM1999a Serial 1657  
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Author Ernest Valveny; Miquel Ferrer edit  openurl
  Title (up) Application of Graph Embedding to Solve Graph Matchin Problems Type Conference Article
  Year 2008 Publication Colloque International Francophone sur l’Ecrit et le Document Abbreviated Journal  
  Volume Issue Pages 13–18  
  Keywords  
  Abstract  
  Address Rouen (France)  
  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 Expedition Conference CIFED’08  
  Notes DAG Approved no  
  Call Number DAG @ dag @ VaF2008 Serial 1063  
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Author Gisel Bastidas-Guacho; Patricio Moreno; Boris X. Vintimilla; Angel Sappa edit  url
doi  openurl
  Title (up) Application on the Loop of Multimodal Image Fusion: Trends on Deep-Learning Based Approaches Type Conference Article
  Year 2023 Publication 13th International Conference on Pattern Recognition Systems Abbreviated Journal  
  Volume 14234 Issue Pages 25–36  
  Keywords  
  Abstract Multimodal image fusion allows the combination of information from different modalities, which is useful for tasks such as object detection, edge detection, and tracking, to name a few. Using the fused representation for applications results in better task performance. There are several image fusion approaches, which have been summarized in surveys. However, the existing surveys focus on image fusion approaches where the application on the loop of multimodal image fusion is not considered. On the contrary, this study summarizes deep learning-based multimodal image fusion for computer vision (e.g., object detection) and image processing applications (e.g., semantic segmentation), that is, approaches where the application module leverages the multimodal fusion process to enhance the final result. Firstly, we introduce image fusion and the existing general frameworks for image fusion tasks such as multifocus, multiexposure and multimodal. Then, we describe the multimodal image fusion approaches. Next, we review the state-of-the-art deep learning multimodal image fusion approaches for vision applications. Finally, we conclude our survey with the trends of task-driven multimodal image fusion.  
  Address Guayaquil; Ecuador; July 2023  
  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 Expedition Conference ICPRS  
  Notes MSIAU Approved no  
  Call Number Admin @ si @ BMV2023 Serial 3932  
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Author M.J. Yzuel; J. Pladellorens; Joan Serrat; A. Dupuy edit  openurl
  Title (up) Application restauration and edge detection techniques in the calculation of left ventricular volumes. Type Conference Article
  Year 1993 Publication Optics in Medicine, Biology and Environmental Research : Selected contributions to the first International Conference on Optics within Life Sciences (OWLS I) Abbreviated Journal  
  Volume Issue Pages 374-375  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Elsevier 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 Expedition Conference  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ YPS1993 Serial 244  
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Author Pierluigi Casale; Oriol Pujol; Petia Radeva edit  url
doi  isbn
openurl 
  Title (up) Approximate Convex Hulls Family for One-Class Cassification Type Conference Article
  Year 2011 Publication 10th International Workshop on Multiple Classifier Systems Abbreviated Journal  
  Volume 6713 Issue Pages 106-115  
  Keywords  
  Abstract In this work, a new method for one-class classification based on the Convex Hull geometric structure is proposed. The new method creates a family of convex hulls able to fit the geometrical shape of the training points. The increased computational cost due to the creation of the convex hull in multiple dimensions is circumvented using random projections. This provides an approximation of the original structure with multiple bi-dimensional views. In the projection planes, a mechanism for noisy points rejection has also been elaborated and evaluated. Results show that the approach performs considerably well with respect to the state the art in one-class classification.  
  Address Napoli, Italy  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Carlo Sansone; Josef Kittler; Fabio Roli  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-21556-8 Medium  
  Area Expedition Conference MCS  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ CPR2011b Serial 1761  
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Author Damian Sojka; Sebastian Cygert; Bartlomiej Twardowski; Tomasz Trzcinski edit   pdf
url  openurl
  Title (up) AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation Type Conference Article
  Year 2023 Publication Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops Abbreviated Journal  
  Volume Issue Pages 3491-3495  
  Keywords  
  Abstract Test-time adaptation is a promising research direction that allows the source model to adapt itself to changes in data distribution without any supervision. Yet, current methods are usually evaluated on benchmarks that are only a simplification of real-world scenarios. Hence, we propose to validate test-time adaptation methods using the recently introduced datasets for autonomous driving, namely CLAD-C and SHIFT. We observe that current test-time adaptation methods struggle to effectively handle varying degrees of domain shift, often resulting in degraded performance that falls below that of the source model. We noticed that the root of the problem lies in the inability to preserve the knowledge of the source model and adapt to dynamically changing, temporally correlated data streams. Therefore, we enhance well-established self-training framework by incorporating a small memory buffer to increase model stability and at the same time perform dynamic adaptation based on the intensity of domain shift. The proposed method, named AR-TTA, outperforms existing approaches on both synthetic and more real-world benchmarks and shows robustness across a variety of TTA scenarios.  
  Address Paris; France; October 2023  
  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 Expedition Conference ICCVW  
  Notes LAMP Approved no  
  Call Number Admin @ si @ SCT2023 Serial 3943  
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Author Hamdi Dibeklioglu; Theo Gevers; Albert Ali Salah edit  doi
isbn  openurl
  Title (up) Are You Really Smiling at Me? Spontaneous versus Posed Enjoyment Smiles Type Conference Article
  Year 2012 Publication 12th European Conference on Computer Vision Abbreviated Journal  
  Volume 7574 Issue III Pages 525-538  
  Keywords  
  Abstract Smiling is an indispensable element of nonverbal social interaction. Besides, automatic distinction between spontaneous and posed expressions is important for visual analysis of social signals. Therefore, in this paper, we propose a method to distinguish between spontaneous and posed enjoyment smiles by using the dynamics of eyelid, cheek, and lip corner movements. The discriminative power of these movements, and the effect of different fusion levels are investigated on multiple databases. Our results improve the state-of-the-art. We also introduce the largest spontaneous/posed enjoyment smile database collected to date, and report new empirical and conceptual findings on smile dynamics. The collected database consists of 1240 samples of 400 subjects. Moreover, it has the unique property of having an age range from 8 to 76 years. Large scale experiments on the new database indicate that eyelid dynamics are highly relevant for smile classification, and there are age-related differences in smile dynamics.  
  Address Florence, Italy  
  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 978-3-642-33711-6 Medium  
  Area Expedition Conference ECCV  
  Notes ALTRES;ISE Approved no  
  Call Number Admin @ si @ DGS2012 Serial 2024  
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Author Bojana Gajic; Ariel Amato; Ramon Baldrich; Joost Van de Weijer; Carlo Gatta edit   pdf
doi  openurl
  Title (up) Area Under the ROC Curve Maximization for Metric Learning Type Conference Article
  Year 2022 Publication CVPR 2022 Workshop on Efficien Deep Learning for Computer Vision (ECV 2022, 5th Edition) Abbreviated Journal  
  Volume Issue Pages  
  Keywords Training; Computer vision; Conferences; Area measurement; Benchmark testing; Pattern recognition  
  Abstract Most popular metric learning losses have no direct relation with the evaluation metrics that are subsequently applied to evaluate their performance. We hypothesize that training a metric learning model by maximizing the area under the ROC curve (which is a typical performance measure of recognition systems) can induce an implicit ranking suitable for retrieval problems. This hypothesis is supported by previous work that proved that a curve dominates in ROC space if and only if it dominates in Precision-Recall space. To test this hypothesis, we design and maximize an approximated, derivable relaxation of the area under the ROC curve. The proposed AUC loss achieves state-of-the-art results on two large scale retrieval benchmark datasets (Stanford Online Products and DeepFashion In-Shop). Moreover, the AUC loss achieves comparable performance to more complex, domain specific, state-of-the-art methods for vehicle re-identification.  
  Address New Orleans, USA; 20 June 2022  
  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 Expedition Conference CVPRW  
  Notes CIC; LAMP; Approved no  
  Call Number Admin @ si @ GAB2022 Serial 3700  
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Author German Ros; Jesus Martinez del Rincon; Gines Garcia-Mateos edit   pdf
url  isbn
openurl 
  Title (up) Articulated Particle Filter for Hand Tracking Type Conference Article
  Year 2012 Publication 21st International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 3581 - 3585  
  Keywords  
  Abstract This paper proposes a new version of Particle Filter, called Articulated Particle Filter – ArPF -, which has been specifically designed for an efficient sampling of hierarchical spaces, generated by articulated objects. Our approach decomposes the articulated motion into layers for efficiency purposes, making use of a careful modeling of the diffusion noise along with its propagation through the articulations. This produces an increase of accuracy and prevent for divergences. The algorithm is tested on hand tracking due to its complex hierarchical articulated nature. With this purpose, a new dataset generation tool for quantitative evaluation is also presented in this paper.  
  Address Tsukuba Science City, Japan  
  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 1051-4651 ISBN 978-1-4673-2216-4 Medium  
  Area Expedition Conference ICPR  
  Notes ADAS Approved no  
  Call Number Admin @ si @ RMG2012 Serial 2031  
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Author David Roche; Debora Gil; Jesus Giraldo edit   pdf
url  openurl
  Title (up) Assessing agonist efficacy in an uncertain Em world Type Conference Article
  Year 2012 Publication 40th Keystone Symposia on mollecular and celular biology Abbreviated Journal  
  Volume Issue Pages 79  
  Keywords  
  Abstract The operational model of agonism has been widely used for the analysis of agonist action since its formulation in 1983. The model includes the Em parameter, which is defined as the maximum response of the system. The methods for Em estimation provide Em values not significantly higher than the maximum responses achieved by full agonists. However, it has been found that that some classes of compounds as, for instance, superagonists and positive allosteric modulators can increase the full agonist maximum response, implying upper limits for Em and thereby posing doubts on the validity of Em estimates. Because of the correlation between Em and operational efficacy, τ, wrong Em estimates will yield wrong τ estimates.
In this presentation, the operational model of agonism and various methods for the simulation of allosteric modulation will be analyzed. Alternatives for curve fitting will be presented and discussed.
 
  Address Fairmont Banff Springs, Banff, Alberta, Canada  
  Corporate Author Keystone Symposia Thesis  
  Publisher Keystone Symposia Place of Publication Editor A. Christopoulus and M. Bouvier  
  Language english Summary Language english Original Title  
  Series Editor Keystone Symposia Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference KSMCB  
  Notes IAM Approved no  
  Call Number IAM @ iam @ RGG2012 Serial 1855  
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