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Author | M. Bressan; Jordi Vitria | ||||
Title | Nonparametric Discriminant Analysis and Nearest Neighbor Classification | Type | Journal Article | ||
Year | 2003 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
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24 | Issue | 15 | Pages | 2743–2749 |
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Abstract | IF: 0.809 | ||||
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Notes | OR;MV | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ BrV2003b | Serial | 367 | ||
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Author | Cristina Cañero; Petia Radeva | ||||
Title | Vesselness enhancement diffusion | Type | Journal Article | ||
Year | 2003 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
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24 | Issue | 16 | Pages | 3141–3151 |
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Abstract | IF: 0.809 | ||||
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Notes | MILAB | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ CaR2003 | Serial | 371 | ||
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Author | David Guillamet; Jordi Vitria | ||||
Title | Evaluation of distance metrics for recognition based on non-negative matrix factorization | Type | Journal Article | ||
Year | 2003 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
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24 | Issue | 9-10 | Pages | 1599 –1605 |
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Abstract | IF: 0.809 | ||||
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Notes | OR;MV | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ GuV2003b | Serial | 380 | ||
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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 |
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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 | Ernest Valveny; Enric Marti | ||||
Title | A model for image generation and symbol recognition through the deformation of lineal shapes | Type | Journal Article | ||
Year | 2003 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
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24 | Issue | 15 | Pages | 2857-2867 |
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Abstract | We describe a general framework for the recognition of distorted images of lineal shapes, which relies on three items: a model to represent lineal shapes and their deformations, a model for the generation of distorted binary images and the combination of both models in a common probabilistic framework, where the generation of deformations is related to an internal energy, and the generation of binary images to an external energy. Then, recognition consists in the minimization of a global energy function, performed by using the EM algorithm. This general framework has been applied to the recognition of hand-drawn lineal symbols in graphic documents. | ||||
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Publisher | Elsevier Science Inc. | Place of Publication | New York, NY, USA | Editor | |
Language | Summary Language | Original Title | |||
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ISSN | 0167-8655 | ISBN | Medium | ||
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Notes | DAG; IAM | Approved | no | ||
Call Number | IAM @ iam @ VAM2003 | Serial | 1653 | ||
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Author | Carolina Malagelada; F.De Lorio; Santiago Segui; S. Mendez; Michal Drozdzal; Jordi Vitria; Petia Radeva; J.Santos; Anna Accarino; Juan R. Malagelada; Fernando Azpiroz | ||||
Title | Functional gut disorders or disordered gut function? Small bowel dysmotility evidenced by an original technique | Type | Journal Article | ||
Year | 2012 | Publication | Neurogastroenterology & Motility | Abbreviated Journal | NEUMOT |
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24 | Issue | 3 | Pages | 223-230 |
Keywords | capsule endoscopy;computer vision analysis;machine learning technique;small bowel motility | ||||
Abstract | JCR Impact Factor 2010: 3.349
Background This study aimed to determine the proportion of cases with abnormal intestinal motility among patients with functional bowel disorders. To this end, we applied an original method, previously developed in our laboratory, for analysis of endoluminal images obtained by capsule endoscopy. This novel technology is based on computer vision and machine learning techniques. Methods The endoscopic capsule (Pillcam SB1; Given Imaging, Yokneam, Israel) was administered to 80 patients with functional bowel disorders and 70 healthy subjects. Endoluminal image analysis was performed with a computer vision program developed for the evaluation of contractile events (luminal occlusions and radial wrinkles), non-contractile patterns (open tunnel and smooth wall patterns), type of content (secretions, chyme) and motion of wall and contents. Normality range and discrimination of abnormal cases were established by a machine learning technique. Specifically, an iterative classifier (one-class support vector machine) was applied in a random population of 50 healthy subjects as a training set and the remaining subjects (20 healthy subjects and 80 patients) as a test set. Key Results The classifier identified as abnormal 29% of patients with functional diseases of the bowel (23 of 80), and as normal 97% of healthy subjects (68 of 70) (P < 0.05 by chi-squared test). Patients identified as abnormal clustered in two groups, which exhibited either a hyper- or a hypodynamic motility pattern. The motor behavior was unrelated to clinical features. Conclusions & Inferences With appropriate methodology, abnormal intestinal motility can be demonstrated in a significant proportion of patients with functional bowel disorders, implying a pathologic disturbance of gut physiology. |
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Publisher | Wiley Online Library | Place of Publication | Editor | ||
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Notes | MILAB; OR; MV | Approved | no | ||
Call Number | Admin @ si @ MLS2012 | Serial | 1830 | ||
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Author | Bogdan Raducanu; Fadi Dornaika | ||||
Title | Texture-independent recognition of facial expressions in image snapshots and videos | Type | Journal Article | ||
Year | 2013 | Publication | Machine Vision and Applications | Abbreviated Journal | MVA |
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24 | Issue | 4 | Pages | 811-820 |
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Abstract | This paper addresses the static and dynamic recognition of basic facial expressions. It has two main contributions. First, we introduce a view- and texture-independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker. We represent the learned facial actions associated with different facial expressions by time series. Second, we compare this dynamic scheme with a static one based on analyzing individual snapshots and show that the former performs better than the latter. We provide evaluations of performance using three subspace learning techniques: linear discriminant analysis, non-parametric discriminant analysis and support vector machines. | ||||
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Publisher | Springer-Verlag | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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ISSN | 0932-8092 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | OR; 600.046; 605.203;MV | Approved | no | ||
Call Number | Admin @ si @ RaD2013 | Serial | 2230 | ||
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Author | Sergio Vera; Debora Gil; Agnes Borras; Marius George Linguraru; Miguel Angel Gonzalez Ballester | ||||
Title | Geometric Steerable Medial Maps | Type | Journal Article | ||
Year | 2013 | Publication | Machine Vision and Applications | Abbreviated Journal | MVA |
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24 | Issue | 6 | Pages | 1255-1266 |
Keywords | Medial Representations ,Medial Manifolds Comparation , Surface , Reconstruction | ||||
Abstract | In order to provide more intuitive and easily interpretable representations of complex shapes/organs, medial manifolds should reach a compromise between simplicity in geometry and capability for restoring the anatomy/shape of the organ/volume. Existing morphological methods show excellent results when applied to 2D objects, but their quality drops across dimensions.
This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoids degenerated medial axis segments. Second, we introduce a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to syn- thetic shapes of known medial geometry. We also show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume. |
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Mubarak Shah | |
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ISSN | 0932-8092 | ISBN | Medium | ||
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Notes | IAM; 605.203; 600.060; 600.044 | Approved | no | ||
Call Number | IAM @ iam @ VGB2013 | Serial | 2192 | ||
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Author | Miguel Oliveira; Victor Santos; Angel Sappa | ||||
Title | Multimodal Inverse Perspective Mapping | Type | Journal Article | ||
Year | 2015 | Publication | Information Fusion | Abbreviated Journal | IF |
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24 | Issue | Pages | 108–121 | |
Keywords | Inverse perspective mapping; Multimodal sensor fusion; Intelligent vehicles | ||||
Abstract | Over the past years, inverse perspective mapping has been successfully applied to several problems in the field of Intelligent Transportation Systems. In brief, the method consists of mapping images to a new coordinate system where perspective effects are removed. The removal of perspective associated effects facilitates road and obstacle detection and also assists in free space estimation. There is, however, a significant limitation in the inverse perspective mapping: the presence of obstacles on the road disrupts the effectiveness of the mapping. The current paper proposes a robust solution based on the use of multimodal sensor fusion. Data from a laser range finder is fused with images from the cameras, so that the mapping is not computed in the regions where obstacles are present. As shown in the results, this considerably improves the effectiveness of the algorithm and reduces computation time when compared with the classical inverse perspective mapping. Furthermore, the proposed approach is also able to cope with several cameras with different lenses or image resolutions, as well as dynamic viewpoints. | ||||
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Notes | ADAS; 600.055; 600.076 | Approved | no | ||
Call Number | Admin @ si @ OSS2015c | Serial | 2532 | ||
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Author | Mohammad Rouhani; Angel Sappa; E. Boyer | ||||
Title | Implicit B-Spline Surface Reconstruction | Type | Journal Article | ||
Year | 2015 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
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24 | Issue | 1 | Pages | 22 - 32 |
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Abstract | This paper presents a fast and flexible curve, and surface reconstruction technique based on implicit B-spline. This representation does not require any parameterization and it is locally supported. This fact has been exploited in this paper to propose a reconstruction technique through solving a sparse system of equations. This method is further accelerated to reduce the dimension to the active control lattice. Moreover, the surface smoothness and user interaction are allowed for controlling the surface. Finally, a novel weighting technique has been introduced in order to blend small patches and smooth them in the overlapping regions. The whole framework is very fast and efficient and can handle large cloud of points with very low computational cost. The experimental results show the flexibility and accuracy of the proposed algorithm to describe objects with complex topologies. Comparisons with other fitting methods highlight the superiority of the proposed approach in the presence of noise and missing data. | ||||
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ISSN | 1057-7149 | ISBN | Medium | ||
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Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ RSB2015 | Serial | 2541 | ||
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Author | Mikhail Mozerov; Joost Van de Weijer | ||||
Title | Accurate stereo matching by two step global optimization | Type | Journal Article | ||
Year | 2015 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
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24 | Issue | 3 | Pages | 1153-1163 |
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Abstract | In stereo matching cost filtering methods and energy minimization algorithms are considered as two different techniques. Due to their global extend energy minimization methods obtain good stereo matching results. However, they tend to fail in occluded regions, in which cost filtering approaches obtain better results. In this paper we intend to combine both approaches with the aim to improve overall stereo matching results. We show that a global optimization with a fully connected model can be solved by cost fil tering methods. Based on this observation we propose to perform stereo matching as a two-step energy minimization algorithm. We consider two MRF models: a fully connected model defined on the complete set of pixels in an image and a conventional locally connected model. We solve the energy minimization problem for the fully connected model, after which the marginal function of the solution is used as the unary potential in the locally connected MRF model. Experiments on the Middlebury stereo datasets show that the proposed method achieves state-of-the-arts results. | ||||
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ISSN | 1057-7149 | ISBN | Medium | ||
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Notes | ISE; LAMP; 600.079; 600.078 | Approved | no | ||
Call Number | Admin @ si @ MoW2015a | Serial | 2568 | ||
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Author | Fahad Shahbaz Khan; Jiaolong Xu; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez | ||||
Title | Recognizing Actions through Action-specific Person Detection | Type | Journal Article | ||
Year | 2015 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
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24 | Issue | 11 | Pages | 4422-4432 |
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Abstract | Action recognition in still images is a challenging problem in computer vision. To facilitate comparative evaluation independently of person detection, the standard evaluation protocol for action recognition uses an oracle person detector to obtain perfect bounding box information at both training and test time. The assumption is that, in practice, a general person detector will provide candidate bounding boxes for action recognition. In this paper, we argue that this paradigm is suboptimal and that action class labels should already be considered during the detection stage. Motivated by the observation that body pose is strongly conditioned on action class, we show that: 1) the existing state-of-the-art generic person detectors are not adequate for proposing candidate bounding boxes for action classification; 2) due to limited training examples, the direct training of action-specific person detectors is also inadequate; and 3) using only a small number of labeled action examples, the transfer learning is able to adapt an existing detector to propose higher quality bounding boxes for subsequent action classification. To the best of our knowledge, we are the first to investigate transfer learning for the task of action-specific person detection in still images. We perform extensive experiments on two benchmark data sets: 1) Stanford-40 and 2) PASCAL VOC 2012. For the action detection task (i.e., both person localization and classification of the action performed), our approach outperforms methods based on general person detection by 5.7% mean average precision (MAP) on Stanford-40 and 2.1% MAP on PASCAL VOC 2012. Our approach also significantly outperforms the state of the art with a MAP of 45.4% on Stanford-40 and 31.4% on PASCAL VOC 2012. We also evaluate our action detection approach for the task of action classification (i.e., recognizing actions without localizing them). For this task, our approach, without using any ground-truth person localization at test tim- , outperforms on both data sets state-of-the-art methods, which do use person locations. | ||||
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ISSN | 1057-7149 | ISBN | Medium | ||
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Notes | ADAS; LAMP; 600.076; 600.079 | Approved | no | ||
Call Number | Admin @ si @ KXR2015 | Serial | 2668 | ||
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Author | Lluis Garrido; M.Guerrieri; Laura Igual | ||||
Title | Image Segmentation with Cage Active Contours | Type | Journal Article | ||
Year | 2015 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
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24 | Issue | 12 | Pages | 5557 - 5566 |
Keywords | Level sets; Mean value coordinates; Parametrized active contours; level sets; mean value coordinates | ||||
Abstract | In this paper, we present a framework for image segmentation based on parametrized active contours. The evolving contour is parametrized according to a reduced set of control points that form a closed polygon and have a clear visual interpretation. The parametrization, called mean value coordinates, stems from the techniques used in computer graphics to animate virtual models. Our framework allows to easily formulate region-based energies to segment an image. In particular, we present three different local region-based energy terms: 1) the mean model; 2) the Gaussian model; 3) and the histogram model. We show the behavior of our method on synthetic and real images and compare the performance with state-of-the-art level set methods. | ||||
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ISSN | 1057-7149 | ISBN | Medium | ||
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Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ GGI2015 | Serial | 2673 | ||
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Author | Mikhail Mozerov; Joost Van de Weijer | ||||
Title | Global Color Sparseness and a Local Statistics Prior for Fast Bilateral Filtering | Type | Journal Article | ||
Year | 2015 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
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24 | Issue | 12 | Pages | 5842-5853 |
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Abstract | The property of smoothing while preserving edges makes the bilateral filter a very popular image processing tool. However, its non-linear nature results in a computationally costly operation. Various works propose fast approximations to the bilateral filter. However, the majority does not generalize to vector input as is the case with color images. We propose a fast approximation to the bilateral filter for color images. The filter is based on two ideas. First, the number of colors, which occur in a single natural image, is limited. We exploit this color sparseness to rewrite the initial non-linear bilateral filter as a number of linear filter operations. Second, we impose a statistical prior to the image values that are locally present within the filter window. We show that this statistical prior leads to a closed-form solution of the bilateral filter. Finally, we combine both ideas into a single fast and accurate bilateral filter for color images. Experimental results show that our bilateral filter based on the local prior yields an extremely fast bilateral filter approximation, but with limited accuracy, which has potential application in real-time video filtering. Our bilateral filter, which combines color sparseness and local statistics, yields a fast and accurate bilateral filter approximation and obtains the state-of-the-art results. | ||||
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ISSN | 1057-7149 | ISBN | Medium | ||
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Notes | LAMP; 600.079;ISE | Approved | no | ||
Call Number | Admin @ si @ MoW2015b | Serial | 2689 | ||
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Author | I. Sorodoc; S. Pezzelle; A. Herbelot; Mariella Dimiccoli; R. Bernardi | ||||
Title | Learning quantification from images: A structured neural architecture | Type | Journal Article | ||
Year | 2018 | Publication | Natural Language Engineering | Abbreviated Journal | NLE |
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24 | Issue | 3 | Pages | 363-392 |
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Abstract | Major advances have recently been made in merging language and vision representations. Most tasks considered so far have confined themselves to the processing of objects and lexicalised relations amongst objects (content words). We know, however, that humans (even pre-school children) can abstract over raw multimodal data to perform certain types of higher level reasoning, expressed in natural language by function words. A case in point is given by their ability to learn quantifiers, i.e. expressions like few, some and all. From formal semantics and cognitive linguistics, we know that quantifiers are relations over sets which, as a simplification, we can see as proportions. For instance, in most fish are red, most encodes the proportion of fish which are red fish. In this paper, we study how well current neural network strategies model such relations. We propose a task where, given an image and a query expressed by an object–property pair, the system must return a quantifier expressing which proportions of the queried object have the queried property. Our contributions are twofold. First, we show that the best performance on this task involves coupling state-of-the-art attention mechanisms with a network architecture mirroring the logical structure assigned to quantifiers by classic linguistic formalisation. Second, we introduce a new balanced dataset of image scenarios associated with quantification queries, which we hope will foster further research in this area. | ||||
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Notes | MILAB; no menciona | Approved | no | ||
Call Number | Admin @ si @ SPH2018 | Serial | 3021 | ||
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