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Author |
Josep Llados; Young-Bin Kwon |
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Title |
Graphics Recognition. Recent Advances and Perspectives |
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Miscellaneous |
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2004 |
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LNCS 3080, ISBN: 3–540–22478–5 |
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DAG @ dag @ LlK2004 |
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515 |
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Author |
Josep Llados; Gemma Sanchez |
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Title |
Graph Matching vs. Graph Parsing in Graphics Recognition: A Combined Approach |
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2004 |
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International Journal of Pattern Recognition and Artificial Intelligence |
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IJPRAI |
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18 |
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3 |
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455–473 |
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DAG; IF: 0.588 |
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DAG @ dag @ LlS2004 |
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445 |
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Sergio Escalera; Petia Radeva |
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Fast greyscale road sign model matching and recognition |
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Miscellaneous |
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2004 |
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CCIA, IOS Press |
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Barcelona, Spain |
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HuPBA; MILAB |
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BCNPCL @ bcnpcl @ EsR2004 |
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469 |
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Author |
Oriol Pujol |
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Title |
A semi-Supervised Statistical Framework and Generative Snakes for IVUS Analysis |
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2004 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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CVC (UAB), Bellaterra |
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Ph.D. thesis |
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Petia Radeva |
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BCNPCL @ bcnpcl @ Puj2004 |
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512 |
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Author |
Jaume Garcia |
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Title |
Generalized Active Shape Models Applied to Cardiac Function Analysis |
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Report |
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2004 |
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CVC Technical Report |
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78 |
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Cardiac Analysis; Deformable Models; Active Contour Models; Active Shape Models; Tagged MRI; HARP; Contrast Echocardiography. |
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Medical imaging is very useful in the assessment and treatment of many diseases. To deal with the great amount of data provided by imaging scanners and extract quantitative information that physicians can interpret, many analysis algorithms have been developed. Any process of analysis always consists of a first step of segmenting some particular structure. In medical imaging, structures are not always well defined and suffer from noise artifacts thus, ordinary segmentation methods are not well suited. The ones that seem to give better results are those based on deformable models. Nevertheless, despite their capability of mixing image features together with smoothness constraints that may compensate for image irregularities, these are naturally local methods, i. e., each node of the active contour evolve taking into account information about its neighbors and some other weak constraints about flexibility and smoothness, but not about the global shape that they should find. Due to the fact that structures to be segmented are the same for all cases but with some inter and intra-patient variation, the incorporation of a priori knowledge about shape in the segmentation method will provide robustness to it. Active Shape Models is an algorithm based on the creation of a shape model called Point Distribution Model. It performs a segmentation using only shapes similar than those previously learned from a training set that capture most of the variation presented by the structure. This algorithm works by updating shape nodes along a normal segment which often can be too restrictive. For this reason we propose a generalization of this algorithm that we call Generalized Active Shape Models and fully integrates the a priori knowledge given by the Point Distribution Model with deformable models or any other appropriate segmentation method. Two different applications to cardiac imaging of this generalized method are developed and promising results are shown. |
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CVC (UAB) |
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Master's thesis |
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IAM @ iam @ Gar2004 |
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1513 |
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Author |
Debora Gil |
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Title |
Geometric Differential Operators for Shape Modelling |
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Book Whole |
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2004 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Medical imaging feeds research in many computer vision and image processing fields: image filtering, segmentation, shape recovery, registration, retrieval and pattern matching. Because of their low contrast changes and large variety of artifacts and noise, medical imaging processing techniques relying on an analysis of the geometry of image level sets rather than on intensity values result in more robust treatment. From the starting point of treatment of intravascular images, this PhD thesis ad- dresses the design of differential image operators based on geometric principles for a robust shape modelling and restoration. Among all fields applying shape recovery, we approach filtering and segmentation of image objects. For a successful use in real images, the segmentation process should go through three stages: noise removing, shape modelling and shape recovery. This PhD addresses all three topics, but for the sake of algorithms as automated as possible, techniques for image processing will be designed to satisfy three main principles: a) convergence of the iterative schemes to non-trivial states avoiding image degeneration to a constant image and representing smooth models of the originals; b) smooth asymptotic behav- ior ensuring stabilization of the iterative process; c) fixed parameter values ensuring equal (domain free) performance of the algorithms whatever initial images/shapes. Our geometric approach to the generic equations that model the different processes approached enables defining techniques satisfying all the former requirements. First, we introduce a new curvature-based geometric flow for image filtering achieving a good compromise between noise removing and resemblance to original images. Sec- ond, we describe a new family of diffusion operators that restrict their scope to image level curves and serve to restore smooth closed models from unconnected sets of points. Finally, we design a regularization of snake (distance) maps that ensures its smooth convergence towards any closed shape. Experiments show that performance of the techniques proposed overpasses that of state-of-the-art algorithms. |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Barcelona (Spain) |
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Jordi Saludes i Closa;Petia Radeva |
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84-933652-0-3 |
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prit |
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IAM; |
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IAM @ iam @ GIL2004 |
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1517 |
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Author |
Aura Hernandez-Sabate; Debora Gil; Petia Radeva; E.N.Nofrerias |
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Title |
Anisotropic processing of image structures for adventitia detection in intravascular ultrasound images |
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Conference Article |
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Year |
2004 |
Publication |
Proc. Computers in Cardiology |
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31 |
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229-232 |
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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 |
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Chicago (USA) |
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IAM; MILAB |
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IAM @ iam @ HGR2004 |
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1555 |
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Author |
Debora Gil; Petia Radeva |
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Title |
A Regularized Curvature Flow Designed for a Selective Shape Restoration |
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Year |
2004 |
Publication |
IEEE Transactions on Image Processing |
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13 |
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1444–1458 |
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Geometric flows, nonlinear filtering, shape recovery. |
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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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IAM;MILAB |
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BCNPCL @ bcnpcl @ GiR2004b |
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491 |
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Author |
Jaume Garcia; Petia Radeva; Francesc Carreras |
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Title |
Combining Spectral and Active Shape methods to Track Tagged MRI |
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2004 |
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Recent Advances in Artificial Intelligence Research and Development |
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37-44 |
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MR; tagged MR; ASM; LV segmentation; motion estimation. |
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Tagged magnetic resonance is a very usefull and unique tool that provides a complete local and global knowledge of the left ventricle (LV) motion. In this article we introduce a method capable of tracking and segmenting the LV. Spectral methods are applied in order to obtain the so called HARP images which encode information about movement and are the base for LV point-tracking. For segmentation we use Active Shapes (ASM) that model LV shape variation in order to overcome possible local misplacements of the boundary. We finally show experiments on both synthetic and real data which appear to be very promising. |
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IOS Press |
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CCIA |
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IAM;MILAB |
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IAM @ iam @ GRC2004 |
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1488 |
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Author |
Debora Gil; Petia Radeva |
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Title |
Shape Restoration via a Regularized Curvature Flow |
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2004 |
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Journal of Mathematical Imaging and Vision |
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21 |
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3 |
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205-223 |
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Any image filtering operator designed for automatic shape restoration should satisfy robustness (whatever the nature and degree of noise is) as well as non-trivial smooth asymptotic behavior. Moreover, a stopping criterion should be determined by characteristics of the evolved image rather than dependent on the number of iterations. Among the several PDE based techniques, curvature flows appear to be highly reliable for strongly noisy images compared to image diffusion processes.
In the present paper, we introduce a regularized curvature flow (RCF) that admits non-trivial steady states. It is based on a measure of the local curve smoothness that takes into account regularity of the curve curvature and serves as stopping term in the mean curvature flow. We prove that this measure decreases over the orbits of RCF, which endows the method with a natural stop criterion in terms of the magnitude of this measure. Further, in its discrete version it produces steady states consisting of piece-wise regular curves. Numerical experiments made on synthetic shapes corrupted with different kinds of noise show the abilities and limitations of each of the current geometric flows and the benefits of RCF. Finally, we present results on real images that illustrate the usefulness of the present approach in practical applications. |
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IAM @ iam @ GiR2004c |
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1532 |
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Author |
Debora Gil; Petia Radeva |
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Title |
Inhibition of False Landmarks |
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2004 |
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Recent Advances in Artificial Intelligence Research and Development |
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233-244 |
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We argue that a corner detector should be based on the degree of continuity of the tangent vector to the image level sets, work on the image domain and need no assumptions on neither the image local structure nor the particular geometry of the corner/junction. An operator measuring the degree of differentiability of the projection matrix on the image gradient fulfills the above requirements. Its high sensitivity to changes in vector directions makes it suitable for landmark location in real images prone to need smoothing to reduce the impact of noise. Because using smoothing kernels leads to corner misplacement, we suggest an alternative fake response remover based on the receptive field inhibition of spurious details. The combination of both orientation discontinuity detection and noise inhibition produce our Inhibition Orientation Energy (IOE) landmark locator. |
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IOS Press |
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Barcelona (Spain) |
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al, J.V. et |
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IAM @ iam @ GiR2004a |
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Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; Antonio Tovar; Vicente del Valle; Aura Hernandez-Sabate; Debora Gil; Petia Radeva |
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Utilización de la Estructura de los Campos Vectoriales para la Detección de la Adventicia en Imágenes de Ecografía Intracoronaria |
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2004 |
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Revista Internacional de Enfermedades Cardiovasculares Revista Española de Cardiología |
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57 |
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2 |
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100 |
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1642 |
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Jordi Gonzalez; Javier Varona; Xavier Roca; Juan J. Villanueva |
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Analysis of Human Walking Based on aSpaces |
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2004 |
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Articulated Motion and Deformable Objects, Third International Workshop, (AMDO 2004), Lecture Notes in Computer Science, F.J. Perales, B.A. Draper (Eds.), 3179:177–188 |
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ISE @ ise @ GVR2004a |
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492 |
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Jordi Gonzalez; Javier Varona; Xavier Roca; Juan J. Villanueva |
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Situation Graph Trees for Human Behavior Modeling |
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2004 |
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7th Catalan Conference for Artificial Intelligence (CCIA’2004) |
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Barcelona (Spain) |
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ISE @ ise @ GVR2004b |
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498 |
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Author |
Georg Langs; Petia Radeva; David Rotger; Francesc Carreras |
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Building and Registering Parameterized 3D Models of Vessel Trees for Visualization during Intervention |
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Miscellaneous |
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2004 |
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17th International Conference on Pattern Recognition, ICPR’04 |
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Abstract |
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Address |
Cambridge, United Kingdom |
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Notes |
MILAB |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ LRR2004b |
Serial |
463 |
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Permanent link to this record |