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	Author	Philippe Dosch; Ernest Valveny
	Title	Report on the Second Symbol Recognition Contest			Type	Book Chapter
	Year	2006	Publication	Graphics Recognition: Ten Years Review and Future Perspectives, W. Liu, J. Llados (Eds.), LNCS 3926: 381–397	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ DoV2006			Serial	691
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	Author	Quan-sen Sun; Pheng-ann Heng; Zhong Jin; De-shen Xia
	Title	Face recognition based on generalized canonical correlation analysis			Type	Book Chapter
	Year	2005	Publication	Advances in Intelligent Computing, Lecture Notes in Computer Science, 3645: 958–967	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Hefei (China)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	Admin @ si @ SHJ2005			Serial	625
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	Author	Quan-sen Sun; Zhong Jin; Pheng-ann Heng; De-shen Xia
	Title	A novel feature fusion method based on partial least squares regression			Type	Book Chapter
	Year	2005	Publication	Pattern Recognition and Data Mining, Lecture Notes in Computer Science, 3686: 268–277	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Bath (United Kingdom)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	Admin @ si @ SJH2005			Serial	626
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	Author	Rain Eric Haamer; Eka Rusadze; Iiris Lusi; Tauseef Ahmed; Sergio Escalera; Gholamreza Anbarjafari
	Title	Review on Emotion Recognition Databases			Type	Book Chapter
	Year	2018	Publication	Human-Robot Interaction: Theory and Application	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	emotion; computer vision; databases
	Abstract	Over the past few decades human-computer interaction has become more important in our daily lives and research has developed in many directions: memory research, depression detection, and behavioural deficiency detection, lie detection, (hidden) emotion recognition etc. Because of that, the number of generic emotion and face databases or those tailored to specific needs have grown immensely large. Thus, a comprehensive yet compact guide is needed to help researchers find the most suitable database and understand what types of databases already exist. In this paper, different elicitation methods are discussed and the databases are primarily organized into neat and informative tables based on the format.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-78923-316-2	Medium
	Area		Expedition		Conference
	Notes	HUPBA; 602.133			Approved	no
	Call Number	Admin @ si @ HRL2018			Serial	3212
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	Author	Raul Gomez; Lluis Gomez; Jaume Gibert; Dimosthenis Karatzas
	Title	Self-Supervised Learning from Web Data for Multimodal Retrieval			Type	Book Chapter
	Year	2019	Publication	Multi-Modal Scene Understanding Book	Abbreviated Journal
	Volume		Issue		Pages	279-306
	Keywords	self-supervised learning; webly supervised learning; text embeddings; multimodal retrieval; multimodal embedding
	Abstract	Self-Supervised learning from multimodal image and text data allows deep neural networks to learn powerful features with no need of human annotated data. Web and Social Media platforms provide a virtually unlimited amount of this multimodal data. In this work we propose to exploit this free available data to learn a multimodal image and text embedding, aiming to leverage the semantic knowledge learnt in the text domain and transfer it to a visual model for semantic image retrieval. We demonstrate that the proposed pipeline can learn from images with associated text without supervision and analyze the semantic structure of the learnt joint image and text embeddingspace. Weperformathoroughanalysisandperformancecomparisonofﬁvedifferentstateof the art text embeddings in three different benchmarks. We show that the embeddings learnt with Web and Social Media data have competitive performances over supervised methods in the text basedimageretrievaltask,andweclearlyoutperformstateoftheartintheMIRFlickrdatasetwhen training in the target data. Further, we demonstrate how semantic multimodal image retrieval can be performed using the learnt embeddings, going beyond classical instance-level retrieval problems. Finally, we present a new dataset, InstaCities1M, composed by Instagram images and their associated texts that can be used for fair comparison of image-text embeddings.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG; 600.129; 601.338; 601.310			Approved	no
	Call Number	Admin @ si @ GGG2019			Serial	3266
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	Author	Salim Jouili; Salvatore Tabbone; Ernest Valveny
	Title	Comparing Graph Similarity Measures for Graphical Recognition			Type	Book Chapter
	Year	2010	Publication	Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers	Abbreviated Journal
	Volume	6020	Issue		Pages	37-48
	Keywords
	Abstract	In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used including line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each graph distance measure depends on the kind of data and the graph representation technique.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-13727-3	Medium
	Area		Expedition		Conference	GREC
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ JTV2010			Serial	2404
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	Author	Salvatore Tabbone; Oriol Ramos Terrades
	Title	An Overview of Symbol Recognition			Type	Book Chapter
	Year	2014	Publication	Handbook of Document Image Processing and Recognition	Abbreviated Journal
	Volume	D	Issue		Pages	523-551
	Keywords	Pattern recognition; Shape descriptors; Structural descriptors; Symbolrecognition; Symbol spotting
	Abstract	According to the Cambridge Dictionaries Online, a symbol is a sign, shape, or object that is used to represent something else. Symbol recognition is a subfield of general pattern recognition problems that focuses on identifying, detecting, and recognizing symbols in technical drawings, maps, or miscellaneous documents such as logos and musical scores. This chapter aims at providing the reader an overview of the different existing ways of describing and recognizing symbols and how the field has evolved to attain a certain degree of maturity.
	Address
	Corporate Author				Thesis
	Publisher	Springer London	Place of Publication		Editor	D. Doermann; K. Tombre
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-0-85729-858-4	Medium
	Area		Expedition		Conference
	Notes	DAG; 600.077			Approved	no
	Call Number	Admin @ si @ TaT2014			Serial	2489
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	Author	Santiago Segui; Laura Igual; Fernando Vilariño; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria
	Title	Diagnostic System for Intestinal Motility Disfunctions Using Video Capsule Endoscopy			Type	Book Chapter
	Year	2008	Publication	Computer Vision Systems. 6th International	Abbreviated Journal
	Volume	5008	Issue		Pages	251–260
	Keywords
	Abstract	Wireless Video Capsule Endoscopy is a clinical technique consisting of the analysis of images from the intestine which are pro- vided by an ingestible device with a camera attached to it. In this paper we propose an automatic system to diagnose severe intestinal motility disfunctions using the video endoscopy data. The system is based on the application of computer vision techniques within a machine learn- ing framework in order to obtain the characterization of diverse motil- ity events from video sequences. We present experimental results that demonstrate the effectiveness of the proposed system and compare them with the ground-truth provided by the gastroenterologists.
	Address	Santorini (Greece)
	Corporate Author				Thesis
	Publisher	Springer-Verlag	Place of Publication	Berlin Heidelberg	Editor	A. Gasteratos, M. Vincze, and J.K. Tsotsos
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-540-79546-9	Medium
	Area	800	Expedition		Conference	ICVS
	Notes	OR; MV; MILAB; SIAI			Approved	no
	Call Number	BCNPCL @ bcnpcl @ SIV2008; IAM @ iam @ SIV2008			Serial	962
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	Author	Santiago Segui; Laura Igual; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria
	Title	A Semi-Supervised Learning Method for Motility Disease Diagnostic			Type	Book Chapter
	Year	2007	Publication	Progress in Pattern Recognition, Image Analysis and Applications, 12th Iberoamerican Congress on Pattern (CIARP 2007), LCNS 4756:773–782, ISBN 978–3–540–76724–4	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	OR;MILAB;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ SIR2007b			Serial	897
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	Author	Sergio Escalera; David M.J. Tax; Oriol Pujol; Petia Radeva; Robert P.W. Duin
	Title	Multi-Class Classification in Image Analysis Via Error-Correcting Output Codes			Type	Book Chapter
	Year	2011	Publication	Innovations in Intelligent Image Analysis	Abbreviated Journal
	Volume	339	Issue		Pages	7-29
	Keywords
	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.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication	Berlin	Editor	H. Kawasnicka; L.Jain
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1860-949X	ISBN	978-3-642-17933-4	Medium
	Area		Expedition		Conference
	Notes	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ ETP2011			Serial	1746
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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
	Title	Introduction to NIPS 2017 Competition Track			Type	Book Chapter
	Year	2018	Publication	The NIPS ’17 Competition: Building Intelligent Systems	Abbreviated Journal
	Volume		Issue		Pages	1-23
	Keywords
	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.
	Address
	Corporate Author				Thesis
	Publisher	Springer	Place of Publication		Editor	Sergio Escalera; Markus Weimer
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-319-94042-7	Medium
	Area		Expedition		Conference
	Notes	HUPBA; no proj			Approved	no
	Call Number	Admin @ si @ EWB2018			Serial	3200
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	Author	Sergio Escalera; Marti Soler; Stephane Ayache; Umut Guçlu; Jun Wan; Meysam Madadi; Xavier Baro; Hugo Jair Escalante; Isabelle Guyon
	Title	ChaLearn Looking at People: Inpainting and Denoising Challenges			Type	Book Chapter
	Year	2019	Publication	The Springer Series on Challenges in Machine Learning	Abbreviated Journal
	Volume		Issue		Pages	23-44
	Keywords
	Abstract	Dealing with incomplete information is a well studied problem in the context of machine learning and computational intelligence. However, in the context of computer vision, the problem has only been studied in specific scenarios (e.g., certain types of occlusions in specific types of images), although it is common to have incomplete information in visual data. This chapter describes the design of an academic competition focusing on inpainting of images and video sequences that was part of the competition program of WCCI2018 and had a satellite event collocated with ECCV2018. The ChaLearn Looking at People Inpainting Challenge aimed at advancing the state of the art on visual inpainting by promoting the development of methods for recovering missing and occluded information from images and video. Three tracks were proposed in which visual inpainting might be helpful but still challenging: human body pose estimation, text overlays removal and fingerprint denoising. This chapter describes the design of the challenge, which includes the release of three novel datasets, and the description of evaluation metrics, baselines and evaluation protocol. The results of the challenge are analyzed and discussed in detail and conclusions derived from this event are outlined.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	HuPBA; no proj			Approved	no
	Call Number	Admin @ si @ ESA2019			Serial	3327
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	Author	Sergio Escalera; Oriol Pujol; Eric Laciar; Jordi Vitria; Esther Pueyo; Petia Radeva
	Title	Classification of Coronary Damage in Chronic Chagasic Patients			Type	Book Chapter
	Year	2010	Publication	Intelligent Systems – From Theory to Practice. Studies in Computational Intelligence	Abbreviated Journal
	Volume	299	Issue		Pages	461-478
	Keywords	Chagas disease; Error-Correcting Output Codes; High resolution ECG; Decoding
	Abstract	Post Conference IEEE-IS 2008 The Chagas’ disease is endemic in all Latin America, affecting millions of people in the continent. In order to diagnose and treat the chagas’ disease, it is important to detect and measure the coronary damage of the patient. In this paper, we analyze and categorize patients into different groups based on the coronary damage produced by the disease. Based on the features of the heart cycle extracted using high resolution ECG, a multi-class scheme of Error-Correcting Output Codes (ECOC)is formulated and successfully applied. The results show that the proposed scheme obtains significant performance improvements compared to previous works and state-of-the-art ECOC designs.
	Address
	Corporate Author				Thesis
	Publisher	Springer-Verlag	Place of Publication		Editor	V. Sgurev, M. Hadjiski (eds)
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	OR;MILAB;HUPBA;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ EPL2010			Serial	1452
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	Author	Sergio Escalera; Oriol Pujol; Petia Radeva
	Title	Decoding of Ternary Error Correcting Output Codes			Type	Book Chapter
	Year	2006	Publication	11th Iberoamerican Congress on Pattern Recognition (CIARP´06), LNCS 4225: 753–763	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Cancun (Mexico)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB;HuPBA			Approved	no
	Call Number	BCNPCL @ bcnpcl @ EPR2006e			Serial	696
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	Author	Sergio Escalera; Oriol Pujol; Petia Radeva
	Title	Robust Complex Salient Regions			Type	Book Chapter
	Year	2007	Publication	3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4478:113–121	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB;HuPBA			Approved	no
	Call Number	BCNPCL @ bcnpcl @ EPR2007b			Serial	906
Permanent link to this record