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Author |
Sergio Escalera; David M.J. Tax; Oriol Pujol; Petia Radeva; Robert P.W. Duin |
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Title |
Multi-Class Classification in Image Analysis Via Error-Correcting Output Codes |
Type |
Book Chapter |
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Year |
2011 |
Publication |
Innovations in Intelligent Image Analysis |
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Volume |
339 |
Issue |
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Pages |
7-29 |
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Abstract |
A common way to model multi-class classification problems is by means of Error-Correcting Output Codes (ECOC). Given a multi-class problem, the ECOC technique designs a codeword for each class, where each position of the code identifies the membership of the class for a given binary problem.A classification decision is obtained by assigning the label of the class with the closest code. In this paper, we overview the state-of-the-art on ECOC designs and test them in real applications. Results on different multi-class data sets show the benefits of using the ensemble of classifiers when categorizing objects in images. |
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Springer Berlin Heidelberg |
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Berlin |
Editor |
H. Kawasnicka; L.Jain |
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ISSN |
1860-949X |
ISBN |
978-3-642-17933-4 |
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MILAB;HuPBA |
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no |
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Call Number |
Admin @ si @ ETP2011 |
Serial |
1746 |
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Author |
Angel Sappa; David Geronimo; Fadi Dornaika; Mohammad Rouhani; Antonio Lopez |
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Title |
Moving object detection from mobile platforms using stereo data registration |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Computational Intelligence paradigms in advanced pattern classification |
Abbreviated Journal |
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Volume |
386 |
Issue |
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Pages |
25-37 |
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Keywords |
pedestrian detection |
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Abstract |
This chapter describes a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three main stages. Initially, feature points are extracted and tracked through consecutive 2D frames. Then, a RANSAC based approach is used for registering two point sets, with known correspondences in the 3D space. The computed 3D rigid displacement is used to map two consecutive 3D point clouds into the same coordinate system by means of the quaternion method. Finally, moving objects correspond to those areas with large 3D registration errors. Experimental results show the viability of the proposed approach to detect moving objects like vehicles or pedestrians in different urban scenarios. |
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Springer Berlin Heidelberg |
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Marek R. Ogiela; Lakhmi C. Jain |
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ISSN |
1860-949X |
ISBN |
978-3-642-24048-5 |
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ADAS |
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no |
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Call Number |
Admin @ si @ SGD2012 |
Serial |
2061 |
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Author |
Ariel Amato; Ivan Huerta; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez |
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Title |
Moving Cast Shadows Detection Methods for Video Surveillance Applications |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Augmented Vision and Reality |
Abbreviated Journal |
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Volume |
6 |
Issue |
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Pages |
23-47 |
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Abstract |
Moving cast shadows are a major concern in today’s performance from broad range of many vision-based surveillance applications because they highly difficult the object classification task. Several shadow detection methods have been reported in the literature during the last years. They are mainly divided into two domains. One usually works with static images, whereas the second one uses image sequences, namely video content. In spite of the fact that both cases can be analogously analyzed, there is a difference in the application field. The first case, shadow detection methods can be exploited in order to obtain additional geometric and semantic cues about shape and position of its casting object (‘shape from shadows’) as well as the localization of the light source. While in the second one, the main purpose is usually change detection, scene matching or surveillance (usually in a background subtraction context). Shadows can in fact modify in a negative way the shape and color of the target object and therefore affect the performance of scene analysis and interpretation in many applications. This chapter wills mainly reviews shadow detection methods as well as their taxonomies related with the second case, thus aiming at those shadows which are associated with moving objects (moving shadows). |
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Springer Berlin Heidelberg |
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ISSN |
2190-5916 |
ISBN |
978-3-642-37840-9 |
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Notes |
ISE; 605.203; 600.049; 302.018; 302.012; 600.078 |
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no |
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Call Number |
Admin @ si @ AHM2014 |
Serial |
2223 |
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Author |
Miquel Ferrer; I. Bardaji; Ernest Valveny; Dimosthenis Karatzas; Horst Bunke |
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Title |
Median Graph Computation by Means of Graph Embedding into Vector Spaces |
Type |
Book Chapter |
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Year |
2013 |
Publication |
Graph Embedding for Pattern Analysis |
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Pages |
45-72 |
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Abstract |
In pattern recognition [8, 14], a key issue to be addressed when designing a system is how to represent input patterns. Feature vectors is a common option. That is, a set of numerical features describing relevant properties of the pattern are computed and arranged in a vector form. The main advantages of this kind of representation are computational simplicity and a well sound mathematical foundation. Thus, a large number of operations are available to work with vectors and a large repository of algorithms for pattern analysis and classification exist. However, the simple structure of feature vectors might not be the best option for complex patterns where nonnumerical features or relations between different parts of the pattern become relevant. |
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Springer New York |
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Editor |
Yun Fu; Yungian Ma |
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978-1-4614-4456-5 |
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Notes |
DAG |
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no |
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Call Number |
Admin @ si @ FBV2013 |
Serial |
2421 |
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Author |
H. Martin Kjer; Jens Fagertun; Sergio Vera; Debora Gil |
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Title |
Medial structure generation for registration of anatomical structures |
Type |
Book Chapter |
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Year |
2017 |
Publication |
Skeletonization, Theory, Methods and Applications |
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Volume |
11 |
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Notes |
IAM; 600.096; 600.075; 600.145 |
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no |
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Call Number |
Admin @ si @ MFV2017a |
Serial |
2935 |
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Author |
David Masip; Agata Lapedriza; Jordi Vitria |
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Title |
Measuring External Face Appearance for Face Classification. |
Type |
Book Chapter |
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Year |
2007 |
Publication |
Face Recognition, Ed. Kresimir Delac and Mislav Grgic, pp. 287–307, ISBN 978–3–902613–03–5, I–Tech Education and Publishing |
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Vienna (Austria) |
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Notes |
OR;MV |
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no |
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Call Number |
BCNPCL @ bcnpcl @ MLV2007b |
Serial |
940 |
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Author |
David Roche; Debora Gil; Jesus Giraldo |
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Title |
Mathematical modeling of G protein-coupled receptor function: What can we learn from empirical and mechanistic models? |
Type |
Book Chapter |
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Year |
2014 |
Publication |
G Protein-Coupled Receptors – Modeling and Simulation Advances in Experimental Medicine and Biology |
Abbreviated Journal |
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Volume |
796 |
Issue |
3 |
Pages |
159-181 |
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Keywords |
β-arrestin; biased agonism; curve fitting; empirical modeling; evolutionary algorithm; functional selectivity; G protein; GPCR; Hill coefficient; intrinsic efficacy; inverse agonism; mathematical modeling; mechanistic modeling; operational model; parameter optimization; receptor dimer; receptor oligomerization; receptor constitutive activity; signal transduction; two-state model |
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Abstract |
Empirical and mechanistic models differ in their approaches to the analysis of pharmacological effect. Whereas the parameters of the former are not physical constants those of the latter embody the nature, often complex, of biology. Empirical models are exclusively used for curve fitting, merely to characterize the shape of the E/[A] curves. Mechanistic models, on the contrary, enable the examination of mechanistic hypotheses by parameter simulation. Regretfully, the many parameters that mechanistic models may include can represent a great difficulty for curve fitting, representing, thus, a challenge for computational method development. In the present study some empirical and mechanistic models are shown and the connections, which may appear in a number of cases between them, are analyzed from the curves they yield. It may be concluded that systematic and careful curve shape analysis can be extremely useful for the understanding of receptor function, ligand classification and drug discovery, thus providing a common language for the communication between pharmacologists and medicinal chemists. |
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Springer Netherlands |
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ISSN |
0065-2598 |
ISBN |
978-94-007-7422-3 |
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Notes |
IAM; 600.075 |
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no |
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Call Number |
IAM @ iam @ RGG2014 |
Serial |
2197 |
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Permanent link to this record |
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Author |
A.Kesidis; Dimosthenis Karatzas |
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Title |
Logo and Trademark Recognition |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
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Volume |
D |
Issue |
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Pages |
591-646 |
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Keywords |
Logo recognition; Logo removal; Logo spotting; Trademark registration; Trademark retrieval systems |
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Abstract |
The importance of logos and trademarks in nowadays society is indisputable, variably seen under a positive light as a valuable service for consumers or a negative one as a catalyst of ever-increasing consumerism. This chapter discusses the technical approaches for enabling machines to work with logos, looking into the latest methodologies for logo detection, localization, representation, recognition, retrieval, and spotting in a variety of media. This analysis is presented in the context of three different applications covering the complete depth and breadth of state of the art techniques. These are trademark retrieval systems, logo recognition in document images, and logo detection and removal in images and videos. This chapter, due to the very nature of logos and trademarks, brings together various facets of document image analysis spanning graphical and textual content, while it links document image analysis to other computer vision domains, especially when it comes to the analysis of real-scene videos and images. |
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Springer London |
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Editor |
D. Doermann; K. Tombre |
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978-0-85729-858-4 |
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Notes |
DAG; 600.077 |
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no |
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Call Number |
Admin @ si @ KeK2014 |
Serial |
2425 |
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Author |
Jose Antonio Rodriguez; Florent Perronnin |
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Title |
Local Gradient Histogram Features for Word Spotting in Unconstrained Handwritten Documents |
Type |
Book Chapter |
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Year |
2008 |
Publication |
Graphics Recognition: Recent Advances and New Opportunities |
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Volume |
5046 |
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Pages |
188–198 |
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Editor |
W. Liu, J. Llados, J.M. Ogier |
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no |
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Admin @ si @ RoP2008a |
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992 |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva |
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Title |
Linear Radial Patterns Characterization for Automatic Detection of Tonic Intestinal Contractions |
Type |
Book Chapter |
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Year |
2006 |
Publication |
11th Iberoamerican Congress on Pattern Recognition |
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Volume |
4225 |
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Pages |
178–187 |
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Abstract |
This work tackles the categorization of general linear radial patterns by means of the valleys and ridges detection and the use of descriptors of directional information, which are provided by steerable filters in different regions of the image. We successfully apply our proposal in the specific case of automatic detection of tonic contractions in video capsule endoscopy, which represent a paradigmatic example of linear radial patterns. |
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Cancun (Mexico) |
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Springer Verlag |
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Berlin Heidelberg |
Editor |
.F. Mart ́ınez-Trinidad et al |
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800 |
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Notes |
MV;OR;MILAB;SIAI |
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no |
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BCNPCL @ bcnpcl @ VSV2006c; IAM @ iam @ VSB2006f |
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728 |
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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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Book Chapter |
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Year |
1994 |
Publication |
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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no |
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IAM @ iam @ MRL1994 |
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1609 |
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Author |
Sergio Escalera; Markus Weimer; Mikhail Burtsev; Valentin Malykh; Varvara Logacheva; Ryan Lowe; Iulian Vlad Serban; Yoshua Bengio; Alexander Rudnicky; Alan W. Black; Shrimai Prabhumoye; Łukasz Kidzinski; Mohanty Sharada; Carmichael Ong; Jennifer Hicks; Sergey Levine; Marcel Salathe; Scott Delp; Iker Huerga; Alexander Grigorenko; Leifur Thorbergsson; Anasuya Das; Kyla Nemitz; Jenna Sandker; Stephen King; Alexander S. Ecker; Leon A. Gatys; Matthias Bethge; Jordan Boyd Graber; Shi Feng; Pedro Rodriguez; Mohit Iyyer; He He; Hal Daume III; Sean McGregor; Amir Banifatemi; Alexey Kurakin; Ian Goodfellow; Samy Bengio |
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Title |
Introduction to NIPS 2017 Competition Track |
Type |
Book Chapter |
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Year |
2018 |
Publication |
The NIPS ’17 Competition: Building Intelligent Systems |
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Volume |
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1-23 |
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Abstract |
Competitions have become a popular tool in the data science community to solve hard problems, assess the state of the art and spur new research directions. Companies like Kaggle and open source platforms like Codalab connect people with data and a data science problem to those with the skills and means to solve it. Hence, the question arises: What, if anything, could NIPS add to this rich ecosystem?
In 2017, we embarked to find out. We attracted 23 potential competitions, of which we selected five to be NIPS 2017 competitions. Our final selection features competitions advancing the state of the art in other sciences such as “Classifying Clinically Actionable Genetic Mutations” and “Learning to Run”. Others, like “The Conversational Intelligence Challenge” and “Adversarial Attacks and Defences” generated new data sets that we expect to impact the progress in their respective communities for years to come. And “Human-Computer Question Answering Competition” showed us just how far we as a field have come in ability and efficiency since the break-through performance of Watson in Jeopardy. Two additional competitions, DeepArt and AI XPRIZE Milestions, were also associated to the NIPS 2017 competition track, whose results are also presented within this chapter. |
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Springer |
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Editor |
Sergio Escalera; Markus Weimer |
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ISBN |
978-3-319-94042-7 |
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Notes |
HUPBA; no proj |
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no |
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Call Number |
Admin @ si @ EWB2018 |
Serial |
3200 |
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Permanent link to this record |
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Author |
Joost Van de Weijer; Fahad Shahbaz Khan; Marc Masana |
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Title |
Interactive Visual and Semantic Image Retrieval |
Type |
Book Chapter |
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Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
Abbreviated Journal |
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Volume |
48 |
Issue |
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Pages |
31-35 |
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Abstract |
One direct consequence of recent advances in digital visual data generation and the direct availability of this information through the World-Wide Web, is a urgent demand for efficient image retrieval systems. The objective of image retrieval is to allow users to efficiently browse through this abundance of images. Due to the non-expert nature of the majority of the internet users, such systems should be user friendly, and therefore avoid complex user interfaces. In this chapter we investigate how high-level information provided by recently developed object recognition techniques can improve interactive image retrieval. Wel apply a bagof- word based image representation method to automatically classify images in a number of categories. These additional labels are then applied to improve the image retrieval system. Next to these high-level semantic labels, we also apply a low-level image description to describe the composition and color scheme of the scene. Both descriptions are incorporated in a user feedback image retrieval setting. The main objective is to show that automatic labeling of images with semantic labels can improve image retrieval results. |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
Angel Sappa; Jordi Vitria |
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ISSN |
1868-4394 |
ISBN |
978-3-642-35931-6 |
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Notes |
CIC; 605.203; 600.048 |
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no |
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Call Number |
Admin @ si @ WKC2013 |
Serial |
2284 |
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Permanent link to this record |
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Author |
David Vazquez; Antonio Lopez; Daniel Ponsa; David Geronimo |
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Title |
Interactive Training of Human Detectors |
Type |
Book Chapter |
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Year |
2013 |
Publication |
Multiodal Interaction in Image and Video Applications |
Abbreviated Journal |
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Volume |
48 |
Issue |
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Pages |
169-182 |
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Keywords |
Pedestrian Detection; Virtual World; AdaBoost; Domain Adaptation |
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Abstract |
Image based human detection remains as a challenging problem. Most promising detectors rely on classifiers trained with labelled samples. However, labelling is a manual labor intensive step. To overcome this problem we propose to collect images of pedestrians from a virtual city, i.e., with automatic labels, and train a pedestrian detector with them, which works fine when such virtual-world data are similar to testing one, i.e., real-world pedestrians in urban areas. When testing data is acquired in different conditions than training one, e.g., human detection in personal photo albums, dataset shift appears. In previous work, we cast this problem as one of domain adaptation and solve it with an active learning procedure. In this work, we focus on the same problem but evaluating a different set of faster to compute features, i.e., Haar, EOH and their combination. In particular, we train a classifier with virtual-world data, using such features and Real AdaBoost as learning machine. This classifier is applied to real-world training images. Then, a human oracle interactively corrects the wrong detections, i.e., few miss detections are manually annotated and some false ones are pointed out too. A low amount of manual annotation is fixed as restriction. Real- and virtual-world difficult samples are combined within what we call cool world and we retrain the classifier with this data. Our experiments show that this adapted classifier is equivalent to the one trained with only real-world data but requiring 90% less manual annotations. |
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Address |
Springer Heidelberg New York Dordrecht London |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1868-4394 |
ISBN |
978-3-642-35931-6 |
Medium |
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Area |
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Expedition |
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Conference |
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Notes |
ADAS; 600.057; 600.054; 605.203 |
Approved |
no |
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Call Number |
VLP2013; ADAS @ adas @ vlp2013 |
Serial |
2193 |
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Permanent link to this record |
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Author |
Ernest Valveny; Oriol Ramos Terrades; Joan Mas; Marçal Rusiñol |
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Title |
Interactive Document Retrieval and Classification. |
Type |
Book Chapter |
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Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
Abbreviated Journal |
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Volume |
48 |
Issue |
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Pages |
17-30 |
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Keywords |
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Abstract |
In this chapter we describe a system for document retrieval and classification following the interactive-predictive framework. In particular, the system addresses two different scenarios of document analysis: document classification based on visual appearance and logo detection. These two classical problems of document analysis are formulated following the interactive-predictive model, taking the user interaction into account to make easier the process of annotating and labelling the documents. A system implementing this model in a real scenario is presented and analyzed. This system also takes advantage of active learning techniques to speed up the task of labelling the documents. |
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Address |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
Angel Sappa; Jordi Vitria |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1868-4394 |
ISBN |
978-3-642-35931-6 |
Medium |
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Area |
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Expedition |
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Conference |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ VRM2013 |
Serial |
2341 |
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Permanent link to this record |