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Author |
Fadi Dornaika; Angel Sappa |
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Title  |
Evaluation of an Appearance-based 3D Face Tracker using Dense 3D Data |
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2008 |
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Machine Vision and Applications |
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19 |
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5-6 |
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427–441 |
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ADAS |
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no |
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ADAS @ adas @ DoS2008b |
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1018 |
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Author |
Fahad Shahbaz Khan; Joost Van de Weijer; Sadiq Ali; Michael Felsberg |
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Title |
Evaluating the impact of color on texture recognition |
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Conference Article |
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2013 |
Publication |
15th International Conference on Computer Analysis of Images and Patterns |
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8047 |
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154-162 |
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Color; Texture; image representation |
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Abstract |
State-of-the-art texture descriptors typically operate on grey scale images while ignoring color information. A common way to obtain a joint color-texture representation is to combine the two visual cues at the pixel level. However, such an approach provides sub-optimal results for texture categorisation task.
In this paper we investigate how to optimally exploit color information for texture recognition. We evaluate a variety of color descriptors, popular in image classification, for texture categorisation. In addition we analyze different fusion approaches to combine color and texture cues. Experiments are conducted on the challenging scenes and 10 class texture datasets. Our experiments clearly suggest that in all cases color names provide the best performance. Late fusion is the best strategy to combine color and texture. By selecting the best color descriptor with optimal fusion strategy provides a gain of 5% to 8% compared to texture alone on scenes and texture datasets. |
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York; UK; August 2013 |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-40260-9 |
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CAIP |
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CIC; 600.048 |
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no |
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Admin @ si @ KWA2013 |
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2263 |
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Author |
Juan Ramon Terven Salinas; Bogdan Raducanu; Maria Elena Meza-de-Luna; Joaquin Salas |
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Title |
Evaluating Real-Time Mirroring of Head Gestures using Smart Glasses |
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Conference Article |
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2015 |
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16th IEEE International Conference on Computer Vision Workshops |
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452-460 |
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Mirroring occurs when one person tends to mimic the non-verbal communication of their counterparts. Even though mirroring is a complex phenomenon, in this study, we focus on the detection of head-nodding as a simple non-verbal communication cue due to its significance as a gesture displayed during social interactions. This paper introduces a computer vision-based method to detect mirroring through the analysis of head gestures using wearable cameras (smart glasses). In addition, we study how such a method can be used to explore perceived competence. The proposed method has been evaluated and the experiments demonstrate how static and wearable cameras seem to be equally effective to gather the information required for the analysis. |
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Santiago de Chile; December 2015 |
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ICCVW |
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LAMP; 600.068; 600.072; |
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Admin @ si @ TRM2015 |
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2722 |
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Author |
Diego Velazquez; Pau Rodriguez; Alexandre Lacoste; Issam H. Laradji; Xavier Roca; Jordi Gonzalez |
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Title |
Evaluating Counterfactual Explainers |
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2023 |
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Transactions on Machine Learning Research |
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TMLR |
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Explainability; Counterfactuals; XAI |
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Explainability methods have been widely used to provide insight into the decisions made by statistical models, thus facilitating their adoption in various domains within the industry. Counterfactual explanation methods aim to improve our understanding of a model by perturbing samples in a way that would alter its response in an unexpected manner. This information is helpful for users and for machine learning practitioners to understand and improve their models. Given the value provided by counterfactual explanations, there is a growing interest in the research community to investigate and propose new methods. However, we identify two issues that could hinder the progress in this field. (1) Existing metrics do not accurately reflect the value of an explainability method for the users. (2) Comparisons between methods are usually performed with datasets like CelebA, where images are annotated with attributes that do not fully describe them and with subjective attributes such as ``Attractive''. In this work, we address these problems by proposing an evaluation method with a principled metric to evaluate and compare different counterfactual explanation methods. The evaluation method is based on a synthetic dataset where images are fully described by their annotated attributes. As a result, we are able to perform a fair comparison of multiple explainability methods in the recent literature, obtaining insights about their performance. We make the code public for the benefit of the research community. |
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ISE |
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no |
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Admin @ si @ VRL2023 |
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3891 |
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Author |
Jose Manuel Alvarez; Theo Gevers; Antonio Lopez |
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Title |
Evaluating Color Representation for Online Road Detection |
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Conference Article |
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Year |
2013 |
Publication |
ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars |
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594-595 |
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Detecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. Most existing algorithms use color to classify pixels as road or background. These algorithms reduce the effect of lighting variations and weather conditions by exploiting the discriminant/invariant properties of different color representations. However, up to date, no comparison between these representations have been conducted. Therefore, in this paper, we perform an evaluation of existing color representations for road detection. More specifically, we focus on color planes derived from RGB data and their most com-
mon combinations. The evaluation is done on a set of 7000 road images acquired
using an on-board camera in different real-driving situations. |
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CVVT:E2M |
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ADAS;ISE |
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no |
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Call Number |
Admin @ si @ AGL2013 |
Serial |
2794 |
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Author |
Koen E.A. van de Sande; Theo Gevers; C.G.M. Snoek |
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Title |
Evaluating Color Descriptors for Object and Scene Recognition |
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Journal Article |
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2010 |
Publication |
IEEE Transaction on Pattern Analysis and Machine Intelligence |
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TPAMI |
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32 |
Issue |
9 |
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1582 - 1596 |
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Abstract |
Impact factor: 5.308
Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been proposed. Because many different descriptors exist, a structured overview is required of color invariant descriptors in the context of image category recognition. Therefore, this paper studies the invariance properties and the distinctiveness of color descriptors (software to compute the color descriptors from this paper is available from http://www.colordescriptors.com) in a structured way. The analytical invariance properties of color descriptors are explored, using a taxonomy based on invariance properties with respect to photometric transformations, and tested experimentally using a data set with known illumination conditions. In addition, the distinctiveness of color descriptors is assessed experimentally using two benchmarks, one from the image domain and one from the video domain. From the theoretical and experimental results, it can be derived that invariance to light intensity changes and light color changes affects category recognition. The results further reveal that, for light intensity shifts, the usefulness of invariance is category-specific. Overall, when choosing a single descriptor and no prior knowledge about the data set and object and scene categories is available, the OpponentSIFT is recommended. Furthermore, a combined set of color descriptors outperforms intensity-based SIFT and improves category recognition by 8 percent on the PASCAL VOC 2007 and by 7 percent on the Mediamill Challenge. |
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0162-8828 |
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ALTRES;ISE |
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no |
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Admin @ si @ SGS2010 |
Serial |
1846 |
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Author |
Carles Sanchez; Oriol Ramos Terrades; Patricia Marquez; Enric Marti; Jaume Rocarias; Debora Gil |
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Title |
Evaluación automática de prácticas en Moodle para el aprendizaje autónomo en Ingenierías |
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Miscellaneous |
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2014 |
Publication |
8th International Congress on University Teaching and Innovation |
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Tarragona; juliol 2014 |
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CIDUI |
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IAM; 600.075;DAG |
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no |
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Admin @ si @ SRM2014 |
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2458 |
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Author |
Silvia Sanchez |
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Title |
Estudio de viabilidad para la inspeccion de cinturones de seguridad en color |
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2000 |
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Technical Report #40 |
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CVC (UAB) |
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Admin @ si @ San2000 |
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341 |
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Author |
Alex Caralps |
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Estudi de viabilitat per la inspeccio automatica de cintes elastiques amb silicona |
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Report |
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2000 |
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CVC Technical Report #45 |
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CVC (UAB) |
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Admin @ si @ Car2000 |
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346 |
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Author |
Simone Balocco; O. Basset; G. Courbebaisse; E. Boni; Alejandro F. Frangi; P. Tortoli; C. Cachard |
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Title |
Estimation Of Viscoelastic Properties Of Vessel Walls Using a Computational Model and Doppler Ultrasound |
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Journal Article |
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2010 |
Publication |
Physics in Medicine and Biology |
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PMB |
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55 |
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12 |
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3557–3575 |
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Abstract |
Human arteries affected by atherosclerosis are characterized by altered wall viscoelastic properties. The possibility of noninvasively assessing arterial viscoelasticity in vivo would significantly contribute to the early diagnosis and prevention of this disease. This paper presents a noniterative technique to estimate the viscoelastic parameters of a vascular wall Zener model. The approach requires the simultaneous measurement of flow variations and wall displacements, which can be provided by suitable ultrasound Doppler instruments. Viscoelastic parameters are estimated by fitting the theoretical constitutive equations to the experimental measurements using an ARMA parameter approach. The accuracy and sensitivity of the proposed method are tested using reference data generated by numerical simulations of arterial pulsation in which the physiological conditions and the viscoelastic parameters of the model can be suitably varied. The estimated values quantitatively agree with the reference values, showing that the only parameter affected by changing the physiological conditions is viscosity, whose relative error was about 27% even when a poor signal-to-noise ratio is simulated. Finally, the feasibility of the method is illustrated through three measurements made at different flow regimes on a cylindrical vessel phantom, yielding a parameter mean estimation error of 25%. |
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MILAB |
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BCNPCL @ bcnpcl @ BBC2010 |
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1312 |
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Author |
Robert Benavente; Maria Vanrell; Ramon Baldrich |
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Title |
Estimation of Fuzzy Sets for Computational Colour Categorization |
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2004 |
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Color Research and Application, 29(5):342–353 (IF: 0.739) |
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CAT @ cat @ BVB2004 |
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484 |
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Youssef El Rhabi; Simon Loic; Brun Luc |
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Estimation de la pose d’une caméra à partir d’un flux vidéo en s’approchant du temps réel |
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Conference Article |
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2015 |
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15ème édition d'ORASIS, journées francophones des jeunes chercheurs en vision par ordinateur ORASIS2015 |
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Augmented Reality; SFM; SLAM; real time pose computation; 2D/3D registration |
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Finding a way to estimate quickly and robustly the pose of an image is essential in augmented reality. Here we will discuss the approach we chose in order to get closer to real time by using SIFT points [4]. We propose a method based on filtering both SIFT points and images on which to focus on. Hence we will focus on relevant data. |
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Amiens; France; June 2015 |
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ORASIS |
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DAG; 600.077 |
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Admin @ si @ RLL2015 |
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2626 |
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Author |
Hassan Ahmed Sial |
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Estimating Light Effects from a Single Image: Deep Architectures and Ground-Truth Generation |
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2021 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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In this thesis, we explore how to estimate the effects of the light interacting with the scene objects from a single image. To achieve this goal, we focus on recovering intrinsic components like reflectance, shading, or light properties such as color and position using deep architectures. The success of these approaches relies on training on large and diversified image datasets. Therefore, we present several contributions on this such as: (a) a data-augmentation technique; (b) a ground-truth for an existing multi-illuminant dataset; (c) a family of synthetic datasets, SID for Surreal Intrinsic Datasets, with diversified backgrounds and coherent light conditions; and (d) a practical pipeline to create hybrid ground-truths to overcome the complexity of acquiring realistic light conditions in a massive way. In parallel with the creation of datasets, we trained different flexible encoder-decoder deep architectures incorporating physical constraints from the image formation models.
In the last part of the thesis, we apply all the previous experience to two different problems. Firstly, we create a large hybrid Doc3DShade dataset with real shading and synthetic reflectance under complex illumination conditions, that is used to train a two-stage architecture that improves the character recognition task in complex lighting conditions of unwrapped documents. Secondly, we tackle the problem of single image scene relighting by extending both, the SID dataset to present stronger shading and shadows effects, and the deep architectures to use intrinsic components to estimate new relit images. |
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September 2021 |
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Ph.D. thesis |
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IMPRIMA |
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Maria Vanrell;Ramon Baldrich |
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978-84-122714-8-5 |
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CIC; |
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Admin @ si @ Sia2021 |
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3607 |
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Author |
Marc Serra |
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Estimating Intrinsic Images from Physical and Categorical Color Cues |
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Report |
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2010 |
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CVC Technical Report |
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151 |
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Master's thesis |
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CIC |
Approved |
no |
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Call Number |
Admin @ si @ Ser2010 |
Serial |
1345 |
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Author |
Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu |
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Title |
Estado del Arte en Sistemas de Vision Artificial para Personas Invidentes |
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Journal |
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Year |
2013 |
Publication |
Komputer Sapiens |
Abbreviated Journal |
KS |
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Volume |
1 |
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Pages |
20-25 |
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OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ TSR2013 |
Serial |
2231 |
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| Permanent link to this record |
