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	Author	Angel Morera; Angel Sanchez; Angel Sappa; Jose F. Velez
	Title	Robust Detection of Outdoor Urban Advertising Panels in Static Images			Type	Conference Article
	Year	2019	Publication	18th International Conference on Practical Applications of Agents and Multi-Agent Systems	Abbreviated Journal
	Volume		Issue		Pages	246-256
	Keywords	Object detection; Urban ads panels; Deep learning; Single Shot Detector (SSD) architecture; Intersection over Union (IoU) metric; Augmented Reality
	Abstract	One interesting publicity application for Smart City environments is recognizing brand information contained in urban advertising panels. For such a purpose, a previous stage is to accurately detect and locate the position of these panels in images. This work presents an effective solution to this problem using a Single Shot Detector (SSD) based on a deep neural network architecture that minimizes the number of false detections under multiple variable conditions regarding the panels and the scene. Achieved experimental results using the Intersection over Union (IoU) accuracy metric make this proposal applicable in real complex urban images.
	Address	Aquila; Italia; June 2019
	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	PAAMS
	Notes	MSIAU; 600.130; 600.122			Approved	no
	Call Number	Admin @ si @ MSS2019			Serial	3270
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	Author	Pierluigi Casale; Oriol Pujol; Petia Radeva
	Title	User Verification From Walking Activity. First Steps Towards a Personal Verification System			Type	Conference Article
	Year	2011	Publication	1st International Conference on Pervasive and Embedded Computing and Communication Systems	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Algarve, Portugal
	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	PECCS
	Notes	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ CPR2011c			Serial	1762
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	Author	Wenjuan Gong; Jürgen Brauer; Michael Arens; Jordi Gonzalez
	Title	Modeling vs. Learning Approaches for Monocular 3D Human Pose Estimation			Type	Conference Article
	Year	2011	Publication	1st IEEE International Workshop on Performance Evaluation on Recognition of Human Actions and Pose Estimation Methods	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	London, 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	PERHAPS
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ GBA2011			Serial	1812
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	Author	Maria Ines Torres; Javier Mikel Olaso; Cesar Montenegro; Riberto Santana; A.Vazquez; Raquel Justo; J.A.Lozano; Stephan Schogl; Gerard Chollet; Nazim Dugan; M.Irvine; N.Glackin; C.Pickard; Anna Esposito; Gennaro Cordasco; Alda Troncone; Dijana Petrovska Delacretaz; Aymen Mtibaa; Mohamed Amine Hmani; M.S.Korsnes; L.J.Martinussen; Sergio Escalera; C.Palmero Cantariño; Olivier Deroo; O.Gordeeva; Jofre Tenorio Laranga; E.Gonzalez Fraile; Begoña Fernandez Ruanova; A.Gonzalez Pinto
	Title	The EMPATHIC project: mid-term achievements			Type	Conference Article
	Year	2019	Publication	12th ACM International Conference on PErvasive Technologies Related to Assistive Environments	Abbreviated Journal
	Volume		Issue		Pages	629-638
	Keywords
	Abstract	Maria Ines Torres; Javier Mikel Olaso, César Montenegro, Riberto Santana, A. Vázquez, Raquel Justo, J. A. Lozano, Stephan Schlögl, Gérard Chollet, Nazim Dugan, M. Irvine, N. Glackin, C. Pickard, Anna Esposito, Gennaro Cordasco, Alda Troncone, Dijana Petrovska-Delacrétaz, Aymen Mtibaa, Mohamed Amine Hmani, M. S. Korsnes, L. J. Martinussen, Sergio Escalera, C. Palmero Cantariño, Olivier Deroo, O. Gordeeva, Jofre Tenorio-Laranga, E. Gonzalez-Fraile, Begoña Fernández-Ruanova, A. Gonzalez-Pinto
	Address	Rhodes Greece; June 2019
	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	PETRA
	Notes	HUPBA; no proj			Approved	no
	Call Number	Admin @ si @ TOM2019			Serial	3325
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	Author	David Vazquez; Antonio Lopez
	Title	Intrusion Classification in Intelligent Video Surveillance Systems			Type	Report
	Year	2008	Publication	Estudis d'Enginyeria Superior en Informática	Abbreviated Journal	UAB
	Volume		Issue		Pages
	Keywords	Human detection; Car detection; Intrusion detection
	Abstract	An intelligent video surveillance system (IVS) is a camera-based installation able to process in real-time the images coming from the cameras. The aim is to automatically warn about different events of interest at the moment they happen. Daview system of Davantis is a com mercial example of IVS system. The problems addressed by any IVS system, and so Daview, are so challenging that none IVS system is perfect, thus, they need continuous improvement. Accordingly, this project aims to study different approaches in order to outperform current Daview performance, in particular, we bet for improving its classification core. We present an in deep study of the state of the art on IVS systems, as well as on how Daview works. Based on that knowledge, we propose four possibilities for improving Daview classification capabilities: improve existent classifiers; improve existing classifiers combination; create new classifiers and create new classifier-based architectures. Our main contribution has been the incorporation of state-of-the-art feature selection and machine learning techniques for the classification tasks, a viewpoint not fully addressed in current Daview system. After a comprehensive quantitative evaluation we will see how one of our proposals clearly outperforms the overall performance of current Daview system. In particular the classification core that we finally propose consists in an AdaBoost One-Against-All architecture that uses appearance and motion features that were already present in current Daview system
	Address	Bellaterra, Spain
	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	PFC
	Notes	ADAS			Approved	no
	Call Number	ADAS @ adas @ VL2008a			Serial	1670
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	Author	S.Grau; Ana Puig; Sergio Escalera; Maria Salamo
	Title	Intelligent Interactive Volume Classification			Type	Conference Article
	Year	2013	Publication	Pacific Graphics	Abbreviated Journal
	Volume	32	Issue	7	Pages	23-28
	Keywords
	Abstract	This paper defines an intelligent and interactive framework to classify multiple regions of interest from the original data on demand, without requiring any preprocessing or previous segmentation. The proposed intelligent and interactive approach is divided in three stages: visualize, training and testing. First, users visualize and label some samples directly on slices of the volume. Training and testing are based on a framework of Error Correcting Output Codes and Adaboost classifiers that learn to classify each region the user has painted. Later, at the testing stage, each classifier is directly applied on the rest of samples and combined to perform multi-class labeling, being used in the final rendering. We also parallelized the training stage using a GPU-based implementation for obtaining a rapid interaction and classification.
	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	978-3-905674-50-7	Medium
	Area		Expedition		Conference	PG
	Notes	HuPBA; 600.046;MILAB			Approved	no
	Call Number	Admin @ si @ GPE2013b			Serial	2355
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	Author	Francesco Ciompi; A. Palaioroutas; M. Loeve; Oriol Pujol; Petia Radeva; H. Tiddens; M. de Bruijne
	Title	Lung Tissue Classification in Severe Advanced Cystic Fibrosis from CT Scans			Type	Conference Article
	Year	2011	Publication	In MICCAI 2011 4th International Workshop on Pulmonary Image Analysis	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Toronto, Canada
	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	PIA
	Notes	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ CPL2011			Serial	1798
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	Author	German Barquero; Johnny Nuñez; Sergio Escalera; Zhen Xu; Wei-Wei Tu; Isabelle Guyon
	Title	Didn’t see that coming: a survey on non-verbal social human behavior forecasting			Type	Conference Article
	Year	2022	Publication	Understanding Social Behavior in Dyadic and Small Group Interactions	Abbreviated Journal
	Volume	173	Issue		Pages	139-178
	Keywords
	Abstract	Non-verbal social human behavior forecasting has increasingly attracted the interest of the research community in recent years. Its direct applications to human-robot interaction and socially-aware human motion generation make it a very attractive field. In this survey, we define the behavior forecasting problem for multiple interactive agents in a generic way that aims at unifying the fields of social signals prediction and human motion forecasting, traditionally separated. We hold that both problem formulations refer to the same conceptual problem, and identify many shared fundamental challenges: future stochasticity, context awareness, history exploitation, etc. We also propose a taxonomy that comprises methods published in the last 5 years in a very informative way and describes the current main concerns of the community with regard to this problem. In order to promote further research on this field, we also provide a summarized and friendly overview of audiovisual datasets featuring non-acted social interactions. Finally, we describe the most common metrics used in this task and their particular issues.
	Address	Virtual; June 2022
	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	PMLR
	Notes	HuPBA; no proj			Approved	no
	Call Number	Admin @ si @ BNE2022			Serial	3766
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	Author	Adam Fodor; Rachid R. Saboundji; Julio C. S. Jacques Junior; Sergio Escalera; David Gallardo Pujol; Andras Lorincz
	Title	Multimodal Sentiment and Personality Perception Under Speech: A Comparison of Transformer-based Architectures			Type	Conference Article
	Year	2022	Publication	Understanding Social Behavior in Dyadic and Small Group Interactions	Abbreviated Journal
	Volume	173	Issue		Pages	218-241
	Keywords
	Abstract	Human-machine, human-robot interaction, and collaboration appear in diverse fields, from homecare to Cyber-Physical Systems. Technological development is fast, whereas real-time methods for social communication analysis that can measure small changes in sentiment and personality states, including visual, acoustic and language modalities are lagging, particularly when the goal is to build robust, appearance invariant, and fair methods. We study and compare methods capable of fusing modalities while satisfying real-time and invariant appearance conditions. We compare state-of-the-art transformer architectures in sentiment estimation and introduce them in the much less explored field of personality perception. We show that the architectures perform differently on automatic sentiment and personality perception, suggesting that each task may be better captured/modeled by a particular method. Our work calls attention to the attractive properties of the linear versions of the transformer architectures. In particular, we show that the best results are achieved by fusing the different architectures{’} preprocessing methods. However, they pose extreme conditions in computation power and energy consumption for real-time computations for quadratic transformers due to their memory requirements. In turn, linear transformers pave the way for quantifying small changes in sentiment estimation and personality perception for real-time social communications for machines and robots.
	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	PMLR
	Notes	HuPBA; no menciona			Approved	no
	Call Number	Admin @ si @ FSJ2022			Serial	3769
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	Author	Dustin Carrion Ojeda; Hong Chen; Adrian El Baz; Sergio Escalera; Chaoyu Guan; Isabelle Guyon; Ihsan Ullah; Xin Wang; Wenwu Zhu
	Title	NeurIPS’22 Cross-Domain MetaDL competition: Design and baseline results			Type	Conference Article
	Year	2022	Publication	Understanding Social Behavior in Dyadic and Small Group Interactions	Abbreviated Journal
	Volume	191	Issue		Pages	24-37
	Keywords
	Abstract	We present the design and baseline results for a new challenge in the ChaLearn meta-learning series, accepted at NeurIPS'22, focusing on “cross-domain” meta-learning. Meta-learning aims to leverage experience gained from previous tasks to solve new tasks efficiently (i.e., with better performance, little training data, and/or modest computational resources). While previous challenges in the series focused on within-domain few-shot learning problems, with the aim of learning efficiently N-way k-shot tasks (i.e., N class classification problems with k training examples), this competition challenges the participants to solve “any-way” and “any-shot” problems drawn from various domains (healthcare, ecology, biology, manufacturing, and others), chosen for their humanitarian and societal impact. To that end, we created Meta-Album, a meta-dataset of 40 image classification datasets from 10 domains, from which we carve out tasks with any number of “ways” (within the range 2-20) and any number of “shots” (within the range 1-20). The competition is with code submission, fully blind-tested on the CodaLab challenge platform. The code of the winners will be open-sourced, enabling the deployment of automated machine learning solutions for few-shot image classification across several domains.
	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	PMLR
	Notes	HUPBA; no menciona			Approved	no
	Call Number	Admin @ si @ CCB2022			Serial	3802
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	Author	Fernando Vilariño
	Title	Dissemination, creation and education from archives: Case study of the collection of Digitized Visual Poems from Joan Brossa Foundation			Type	Conference Article
	Year	2016	Publication	International Workshop on Poetry: Archives, Poetries and Receptions	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Barcelona; Spain; October 2016
	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	POETRY
	Notes	MV; 600.097;SIAI			Approved	no
	Call Number	Admin @ si @Vil2016b			Serial	2805
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	Author	Miguel Oliveira; V.Santos; Angel Sappa
	Title	Short term path planning using a multiple hypothesis evaluation approach for an autonomous driving competition			Type	Conference Article
	Year	2012	Publication	IEEE 4th Workshop on Planning, Perception and Navigation for Intelligent Vehicles	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Algarve; Portugal
	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	PPNIV
	Notes	ADAS			Approved	no
	Call Number	Admin @ si @ OSS2012c			Serial	2159
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	Author	N. Serrano; L. Tarazon; D. Perez; Oriol Ramos Terrades; S. Juan
	Title	The GIDOC Prototype			Type	Conference Article
	Year	2010	Publication	10th International Workshop on Pattern Recognition in Information Systems	Abbreviated Journal
	Volume		Issue		Pages	82-89
	Keywords
	Abstract	Transcription of handwritten text in (old) documents is an important, time-consuming task for digital libraries. It might be carried out by first processing all document images off-line, and then manually supervising system transcriptions to edit incorrect parts. However, current techniques for automatic page layout analysis, text line detection and handwriting recognition are still far from perfect, and thus post-editing system output is not clearly better than simply ignoring it. A more effective approach to transcribe old text documents is to follow an interactive- predictive paradigm in which both, the system is guided by the user, and the user is assisted by the system to complete the transcription task as efficiently as possible. Following this approach, a system prototype called GIDOC (Gimp-based Interactive transcription of old text DOCuments) has been developed to provide user-friendly, integrated support for interactive-predictive layout analysis, line detection and handwriting transcription. GIDOC is designed to work with (large) collections of homogeneous documents, that is, of similar structure and writing styles. They are annotated sequentially, by (par- tially) supervising hypotheses drawn from statistical models that are constantly updated with an increasing number of available annotated documents. And this is done at different annotation levels. For instance, at the level of page layout analysis, GIDOC uses a novel text block detection method in which conventional, memoryless techniques are improved with a “history” model of text block positions. Similarly, at the level of text line image transcription, GIDOC includes a handwriting recognizer which is steadily improved with a growing number of (partially) supervised transcriptions.
	Address	Funchal, Portugal
	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	978-989-8425-14-0	Medium
	Area		Expedition		Conference	PRIS
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ STP2010			Serial	1868
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	Author	Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti
	Title	A Case Study of Pattern Recognition: Symbol Recognition in Graphic Documentsa			Type	Conference Article
	Year	2003	Publication	Proceedings of Pattern Recognition in Information Systems	Abbreviated Journal
	Volume		Issue		Pages	1-13
	Keywords
	Abstract
	Address	Angers, France
	Corporate Author				Thesis
	Publisher	ICEIS Press	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	972-98816-3-4	Medium
	Area		Expedition		Conference	PRIS'03
	Notes	DAG;IAM;			Approved	no
	Call Number	IAM @ iam @ LVS2003			Serial	1576
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	Author	Alejandro Tabas; Emili Balaguer-Ballester; Laura Igual
	Title	Spatial Discriminant ICA for RS-fMRI characterisation			Type	Conference Article
	Year	2014	Publication	4th International Workshop on Pattern Recognition in Neuroimaging	Abbreviated Journal
	Volume		Issue		Pages	1-4
	Keywords
	Abstract	Resting-State fMRI (RS-fMRI) is a brain imaging technique useful for exploring functional connectivity. A major point of interest in RS-fMRI analysis is to isolate connectivity patterns characterising disorders such as for instance ADHD. Such characterisation is usually performed in two steps: first, all connectivity patterns in the data are extracted by means of Independent Component Analysis (ICA); second, standard statistical tests are performed over the extracted patterns to find differences between control and clinical groups. In this work we introduce a novel, single-step, approach for this problem termed Spatial Discriminant ICA. The algorithm can efficiently isolate networks of functional connectivity characterising a clinical group by combining ICA and a new variant of the Fisher’s Linear Discriminant also introduced in this work. As the characterisation is carried out in a single step, it potentially provides for a richer characterisation of inter-class differences. The algorithm is tested using synthetic and real fMRI data, showing promising results in both experiments.
	Address	Tübingen; June 2014
	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	978-1-4799-4150-6	Medium
	Area		Expedition		Conference	PRNI
	Notes	OR;MILAB			Approved	no
	Call Number	Admin @ si @ TBI2014			Serial	2493
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