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Author |
Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez |
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Title |
Natural Language Descriptions of Human Behavior from Video Sequences |
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Conference Article |
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2007 |
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Advances in Artificial Intelligence, 30th Annual Conference on Artificial Intelligence |
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4667 |
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279–292 |
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KI |
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ISE |
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ISE @ ise @ FBR2007b |
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921 |
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Author |
Bogdan Raducanu; Jordi Vitria |
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Title |
Incremental Subspace Learning for Cognitive Visual Processes |
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Conference Article |
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2007 |
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Advances in Brain, Vision and Artificial Intelligence, 2nd International Symposium |
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4729 |
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214–223 |
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Naples (Italy) |
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BVAI’07 |
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OR;MV |
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no |
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BCNPCL @ bcnpcl @ RaV2007b |
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901 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
Improving Appearance-Based 3D Face Tracking Using Sparse Stereo Data |
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Conference Article |
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2007 |
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Advances in Computer Graphics and Computer Vision, |
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354–366 |
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Springer Verlag |
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J. Braz, A. Ranchordas, H. Araujo and J. Jorge, |
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VISAPP |
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ADAS |
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no |
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ADAS @ adas @ DoS2007d |
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1046 |
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Author |
Fadi Dornaika; Bogdan Raducanu |
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Title |
Subtle Facial Expression Recognition in Still Images and Videos |
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2011 |
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Advances in Face Image Analysis: Techniques and Technologies |
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14 |
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259-277 |
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This chapter addresses the recognition of basic facial expressions. It has three main contributions. First, the authors introduce a view- and texture independent schemes that exploits facial action parameters estimated by an appearance-based 3D face tracker. they represent the learned facial actions associated with different facial expressions by time series. Two dynamic recognition schemes are proposed: (1) the first is based on conditional predictive models and on an analysis-synthesis scheme, and (2) the second is based on examples allowing straightforward use of machine learning approaches. Second, the authors propose an efficient recognition scheme based on the detection of keyframes in videos. Third, the authors compare the dynamic scheme with a static one based on analyzing individual snapshots and show that in general the former performs better than the latter. The authors then provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). |
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IGI-Global |
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New York, USA |
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Yu-Jin Zhang |
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978-1-6152-0991-0 |
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OR;MV |
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no |
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Admin @ si @ DoR2011 |
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1751 |
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Author |
Jun Wan; Guodong Guo; Sergio Escalera; Hugo Jair Escalante; Stan Z Li |
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Title |
Advances in Face Presentation Attack Detection |
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Book Whole |
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Year |
2023 |
Publication |
Advances in Face Presentation Attack Detection |
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HUPBA |
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no |
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Admin @ si @ WGE2023a |
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3955 |
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Author |
Jun Wan; Guodong Guo; Sergio Escalera; Hugo Jair Escalante; Stan Z Li |
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Title |
Face Presentation Attack Detection (PAD) Challenges |
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Book Chapter |
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Year |
2023 |
Publication |
Advances in Face Presentation Attack Detection |
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17–35 |
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In recent years, the security of face recognition systems has been increasingly threatened. Face Anti-spoofing (FAS) is essential to secure face recognition systems primarily from various attacks. In order to attract researchers and push forward the state of the art in Face Presentation Attack Detection (PAD), we organized three editions of Face Anti-spoofing Workshop and Competition at CVPR 2019, CVPR 2020, and ICCV 2021, which have attracted more than 800 teams from academia and industry, and greatly promoted the algorithms to overcome many challenging problems. In this chapter, we introduce the detailed competition process, including the challenge phases, timeline and evaluation metrics. Along with the workshop, we will introduce the corresponding dataset for each competition including data acquisition details, data processing, statistics, and evaluation protocol. Finally, we provide the available link to download the datasets used in the challenges. |
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SLCV |
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HUPBA |
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no |
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Admin @ si @ WGE2023b |
Serial |
3956 |
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Author |
Jun Wan; Guodong Guo; Sergio Escalera; Hugo Jair Escalante; Stan Z Li |
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Title |
Best Solutions Proposed in the Context of the Face Anti-spoofing Challenge Series |
Type |
Book Chapter |
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Year |
2023 |
Publication |
Advances in Face Presentation Attack Detection |
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37–78 |
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The PAD competitions we organized attracted more than 835 teams from home and abroad, most of them from the industry, which shows that the topic of face anti-spoofing is closely related to daily life, and there is an urgent need for advanced algorithms to solve its application needs. Specifically, the Chalearn LAP multi-modal face anti-spoofing attack detection challenge attracted more than 300 teams for the development phase with a total of 13 teams qualifying for the final round; the Chalearn Face Anti-spoofing Attack Detection Challenge attracted 340 teams in the development stage, and finally, 11 and 8 teams have submitted their codes in the single-modal and multi-modal face anti-spoofing recognition challenges, respectively; the 3D High-Fidelity Mask Face Presentation Attack Detection Challenge attracted 195 teams for the development phase with a total of 18 teams qualifying for the final round. All the results were verified and re-run by the organizing team, and the results were used for the final ranking. In this chapter, we briefly the methods developed by the teams participating in each competition, and introduce the algorithm details of the top-three ranked teams in detail. |
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HUPBA |
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no |
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Admin @ si @ WGE2023d |
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3958 |
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Author |
Jun Wan; Guodong Guo; Sergio Escalera; Hugo Jair Escalante; Stan Z Li |
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Title |
Face Anti-spoofing Progress Driven by Academic Challenges |
Type |
Book Chapter |
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Year |
2023 |
Publication |
Advances in Face Presentation Attack Detection |
Abbreviated Journal |
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1–15 |
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With the ubiquity of facial authentication systems and the prevalence of security cameras around the world, the impact that facial presentation attack techniques may have is huge. However, research progress in this field has been slowed by a number of factors, including the lack of appropriate and realistic datasets, ethical and privacy issues that prevent the recording and distribution of facial images, the little attention that the community has given to potential ethnic biases among others. This chapter provides an overview of contributions derived from the organization of academic challenges in the context of face anti-spoofing detection. Specifically, we discuss the limitations of benchmarks and summarize our efforts in trying to boost research by the community via the participation in academic challenges |
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SLCV |
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HUPBA |
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Admin @ si @ WGE2023c |
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3957 |
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Author |
Quan-sen Sun; Pheng-ann Heng; Zhong Jin; De-shen Xia |
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Title |
Face recognition based on generalized canonical correlation analysis |
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2005 |
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Advances in Intelligent Computing, Lecture Notes in Computer Science, 3645: 958–967 |
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Hefei (China) |
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Admin @ si @ SHJ2005 |
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625 |
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Author |
Jiaolong Xu; Sebastian Ramos; Xu Hu; David Vazquez; Antonio Lopez |
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Title |
Multi-task Bilinear Classifiers for Visual Domain Adaptation |
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2013 |
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Advances in Neural Information Processing Systems Workshop |
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Domain Adaptation; Pedestrian Detection; ADAS |
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We propose a method that aims to lessen the significant accuracy degradation
that a discriminative classifier can suffer when it is trained in a specific domain (source domain) and applied in a different one (target domain). The principal reason for this degradation is the discrepancies in the distribution of the features that feed the classifier in different domains. Therefore, we propose a domain adaptation method that maps the features from the different domains into a common subspace and learns a discriminative domain-invariant classifier within it. Our algorithm combines bilinear classifiers and multi-task learning for domain adaptation.
The bilinear classifier encodes the feature transformation and classification
parameters by a matrix decomposition. In this way, specific feature transformations for multiple domains and a shared classifier are jointly learned in a multi-task learning framework. Focusing on domain adaptation for visual object detection, we apply this method to the state-of-the-art deformable part-based model for cross domain pedestrian detection. Experimental results show that our method significantly avoids the domain drift and improves the accuracy when compared to several baselines. |
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Lake Tahoe; Nevada; USA; December 2013 |
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NIPSW |
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ADAS; 600.054; 600.057; 601.217;ISE |
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ADAS @ adas @ XRH2013 |
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2340 |
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Author |
Enric Marti; Jordi Regincos; Juan Jose Villanueva; Jaime Lopez-Krahe |
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Title |
Line drawing interpretation as polyhedral objects to man-machine interaction in CAD systems |
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1994 |
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Advances in Pattern Recognition and Image Analysis, |
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158-169 |
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World Scientific Pub. |
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981-02-1872-9 |
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IAM;ISE |
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IAM @ iam @ MRL1994 |
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1609 |
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Author |
David Guillamet; Jordi Vitria |
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Title |
Local Discriminant Regions Using Support Vector Machines for Object Recognition. |
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Miscellaneous |
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2000 |
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Advances in Pattern Recognition, Lecture Notes in Computer Science 1876: 550–559, Springer Verlag. |
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OR;MV |
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BCNPCL @ bcnpcl @ GuV2000 a |
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240 |
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Author |
V. Valev; Petia Radeva |
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Title |
Determining Structural Description by Boolean Formulas. |
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1992 |
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Advances in Structural and Syntactic Pattern Recognition |
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5 |
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131–140 |
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Pattern recognition is an active area of research with many applications, some of which have reached commercial maturity. Structural and syntactic methods are very powerful. They are based on symbolic data structures together with matching, parsing, and reasoning procedures that are able to infer interpretations of complex input patterns.
This book gives an overview of the latest developments and achievements in the field. |
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World Scientific |
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H. Bunke |
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Machine Perception and Artificial Intelligence: |
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978-981-279-791-9 |
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MILAB |
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BCNPCL @ bcnpcl @ VaR1992c |
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254 |
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Aleksandr Setkov; Fabio Martinez Carillo; Michele Gouiffes; Christian Jacquemin; Maria Vanrell; Ramon Baldrich |
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DAcImPro: A Novel Database of Acquired Image Projections and Its Application to Object Recognition |
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2015 |
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Advances in Visual Computing. Proceedings of 11th International Symposium, ISVC 2015 Part II |
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9475 |
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463-473 |
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Projector-camera systems; Feature descriptors; Object recognition |
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Projector-camera systems are designed to improve the projection quality by comparing original images with their captured projections, which is usually complicated due to high photometric and geometric variations. Many research works address this problem using their own test data which makes it extremely difficult to compare different proposals. This paper has two main contributions. Firstly, we introduce a new database of acquired image projections (DAcImPro) that, covering photometric and geometric conditions and providing data for ground-truth computation, can serve to evaluate different algorithms in projector-camera systems. Secondly, a new object recognition scenario from acquired projections is presented, which could be of a great interest in such domains, as home video projections and public presentations. We show that the task is more challenging than the classical recognition problem and thus requires additional pre-processing, such as color compensation or projection area selection. |
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Springer International Publishing |
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LNCS |
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0302-9743 |
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978-3-319-27862-9 |
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ISVC |
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CIC |
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no |
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Admin @ si @ SMG2015 |
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2736 |
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Enric Marti; Petia Radeva; Ricardo Toledo; Jordi Vitria |
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Experiencia de aplicación de la metodología de aprendizaje por proyectos en asignaturas de Ingeniería Informática para una mejor adaptación a los créditos ECTS i al Espacio Europeo de Educación Superior |
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Miscellaneous |
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2005 |
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Agencia de Gestio d´Ajuts Universitaris I de Recerca (AGAUR) |
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Agencia de Gestio d´Ajuts Universitaris I de Recerca (AGAUR) |
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Notes |
IAM;RV;OR;MILAB;ADAS;MV |
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Call Number |
IAM @ iam @ MRT2005 |
Serial |
1608 |
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