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	Author	Fernando Vilariño
	Title	Library Living Lab, Numérisation 3D des chapiteaux du cloître de Saint-Cugat : des citoyens co- créant le nouveau patrimoine culturel numérique			Type	Conference Article
	Year	2019	Publication	Intersectorialité et approche Living Labs. Entretiens Jacques-Cartier	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Montreal; Canada; December 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
	Notes	MV; DAG; 600.140; 600.121;SIAI			Approved	no
	Call Number	Admin @ si @ Vil2019a			Serial	3457
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	Author	Fernando Vilariño
	Title	Public Libraries Exploring how technology transforms the cultural experience of people			Type	Conference Article
	Year	2019	Publication	Workshop on Social Impact of AI. Open Living Lab Days Conference.	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Thessaloniki; Grecia; September 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
	Notes	MV; DAG; 600.140; 600.121;SIAI			Approved	no
	Call Number	Admin @ si @ Vil2019b			Serial	3458
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	Author	Fernando Vilariño
	Title	Unveiling the Social Impact of AI			Type	Conference Article
	Year	2020	Publication	Workshop at Digital Living Lab Days Conference	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	September 2020
	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	MV; DAG; 600.121; 600.140;SIAI			Approved	no
	Call Number	Admin @ si @ Vil2020			Serial	3459
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	Author	Fernando Vilariño
	Title	3D Scanning of Capitals at Library Living Lab			Type	Book Whole
	Year	2019	Publication	“Living Lab Projects 2019”. ENoLL.	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	MV; DAG; 600.140; 600.121;SIAI			Approved	no
	Call Number	Admin @ si @ Vil2019c			Serial	3463
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	Author	Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; C. Malagelada; Petia Radeva
	Title	Linear Radial Patterns Characterization for Automatic Detection of Tonic Intestinal Contractions			Type	Book Chapter
	Year	2006	Publication	11th Iberoamerican Congress on Pattern Recognition	Abbreviated Journal
	Volume	4225	Issue		Pages	178–187
	Keywords
	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.
	Address	Cancun (Mexico)
	Corporate Author				Thesis
	Publisher	Springer Verlag	Place of Publication	Berlin Heidelberg	Editor	.F. Mart ́ınez-Trinidad et al
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area	800	Expedition		Conference
	Notes	MV;OR;MILAB;SIAI			Approved	no
	Call Number	BCNPCL @ bcnpcl @ VSV2006c; IAM @ iam @ VSB2006f			Serial	728
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	Author	Santiago Segui; Laura Igual; Fernando Vilariño; Petia Radeva; C. 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	Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
	Title	Current Challenges on Polyp Detection in Colonoscopy Videos: From Region Segmentation to Region Classification. a Pattern Recognition-based Approach.ased Approach			Type	Conference Article
	Year	2011	Publication	2nd International Workshop on Medical Image Analysis and Descriptionfor Diagnosis Systems	Abbreviated Journal
	Volume		Issue		Pages	62-71
	Keywords	Medical Imaging, Colonoscopy, Pattern Recognition, Segmentation, Polyp Detection, Region Description, Machine Learning, Real-time.
	Abstract	In this paper we present our approach on real-time polyp detection in colonoscopy videos. Our method consists of three stages: Image Segmentation, Region Description and Image Classification. Taking into account the constraints of our project, we introduce our segmentation system that is based on the model of appearance of the polyp that we have defined after observing real videos from colonoscopy processes. The output of this stage will ideally be a low number of regions of which one of them should cover the whole polyp region (if there is one in the image). This regions will be described in terms of features and, as a result of a machine learning schema, classified based on the values that they have for the several features that we will use on their description. Although we are still on the early stages of the project, we present some preliminary segmentation results that indicates that we are going in a good direction.
	Address	Rome, Italy
	Corporate Author				Thesis
	Publisher	SciTePress	Place of Publication		Editor	Djemal, Khalifa
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area	800	Expedition		Conference	MIAD
	Notes	MV;SIAI			Approved	no
	Call Number	IAM @ iam @ BSV2011a			Serial	1695
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	Author	Farhan Riaz; Fernando Vilariño; Mario Dinis-Ribeiro; Miguel Coimbraln
	Title	Identifying Potentially Cancerous Tissues in Chromoendoscopy Images			Type	Conference Article
	Year	2011	Publication	5th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	6669	Issue		Pages	709-716
	Keywords	Endoscopy, Computer Assisted Diagnosis, Gradient.
	Abstract	The dynamics of image acquisition conditions for gastroenterology imaging scenarios pose novel challenges for automatic computer assisted decision systems. Such systems should have the ability to mimic the tissue characterization of the physicians. In this paper, our objective is to compare some feature extraction methods to classify a Chromoendoscopy image into two different classes: Normal and Potentially cancerous. Results show that LoG filters generally give best classification accuracy among the other feature extraction methods considered.
	Address	Las Palmas de Gran Canaria. Spain
	Corporate Author				Thesis
	Publisher	Springer	Place of Publication	Berlin	Editor	J. Vitria, J.M. Sanches, and M. Hernandez
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-642-21256-7	Medium
	Area	800	Expedition		Conference	IbPRIA
	Notes	MV;SIAI			Approved	no
	Call Number	Admin @ si @ RVD2011; IAM @ iam @ RVD2011			Serial	1726
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	Author	Fernando Vilariño; Debora Gil; Petia Radeva
	Title	A Novel FLDA Formulation for Numerical Stability Analysis			Type	Book Chapter
	Year	2004	Publication	Recent Advances in Artificial Intelligence Research and Development	Abbreviated Journal
	Volume	113	Issue		Pages	77-84
	Keywords	Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision
	Abstract	Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision.
	Address
	Corporate Author				Thesis
	Publisher	IOS Press	Place of Publication		Editor	J. Vitrià, P. Radeva and I. Aguiló
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-58603-466-5	Medium
	Area		Expedition		Conference
	Notes	MV;IAM;MILAB;SIAI			Approved	no
	Call Number	IAM @ iam @ VGR2004			Serial	1663
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	Author	Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; C. Malagelada; Petia Radeva
	Title	A Machine Learning framework using SOMs: Applications in the Intestinal Motility Assessment			Type	Book Chapter
	Year	2006	Publication	11th Iberoamerican Congress on Pattern Recognition	Abbreviated Journal
	Volume	4225	Issue		Pages	188–197
	Keywords
	Abstract	Small Bowel Motility Assessment by means of Wireless Capsule Video Endoscopy constitutes a novel clinical methodology in which a capsule with a micro-camera attached to it is swallowed by the patient, emitting a RF signal which is recorded as a video of its trip throughout the gut. In order to overcome the main drawbacks associated with this technique -mainly related to the large amount of visualization time required-, our efforts have been focused on the development of a machine learning system, built up in sequential stages, which provides the specialists with the useful part of the video, rejecting those parts not valid for analysis. We successfully used Self Organized Maps in a general semi-supervised framework with the aim of tackling the different learning stages of our system. The analysis of the diverse types of images and the automatic detection of intestinal contractions is performed under the perspective of intestinal motility assessment in a clinical environment.
	Address	Cancun (Mexico)
	Corporate Author				Thesis
	Publisher	Springer Verlag	Place of Publication	Berlin-Heidelberg	Editor	J.P. Martinez–Trinidad et al
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area	800	Expedition		Conference	CIARP06
	Notes	MV;OR;MILAB;SIAI			Approved	no
	Call Number	BCNPCL @ bcnpcl @ VSV2006d; IAM @ iam @ VSV2006e			Serial	729
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	Author	Jorge Bernal; Fernando Vilariño; F. Javier Sanchez
	Title	Towards Intelligent Systems for Colonoscopy			Type	Book Chapter
	Year	2011	Publication	Colonoscopy	Abbreviated Journal
	Volume	1	Issue		Pages	257-282
	Keywords
	Abstract	In this chapter we present tools that can be used to build intelligent systems for colonoscopy. The idea is, by using methods based on computer vision and artiﬁcial intelligence, add signiﬁcant value to the colonoscopy procedure. Intelligent systems are being used to assist in other medical interventions
	Address
	Corporate Author				Thesis
	Publisher	Intech	Place of Publication		Editor	Paul Miskovitz
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-953-307-568-6	Medium
	Area	800	Expedition		Conference
	Notes	MV;SIAI			Approved	no
	Call Number	IAM @ iam @ BVS2011			Serial	1697
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	Author	Fernando Vilariño
	Title	A Machine Learning Approach for Intestinal Motility Assessment with Capsule Endoscopy			Type	Book Whole
	Year	2006	Publication	PhD Thesis, Universitat Autonoma de Barcelona-CVC	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Intestinal motility assessment with video capsule endoscopy arises as a novel and challenging clinical fieldwork. This technique is based on the analysis of the patterns of intestinal contractions obtained by labelling all the motility events present in a video provided by a capsule with a wireless micro-camera, which is ingested by the patient. However, the visual analysis of these video sequences presents several im- portant drawbacks, mainly related to both the large amount of time needed for the visualization process, and the low prevalence of intestinal contractions in video. In this work we propose a machine learning system to automatically detect the intestinal contractions in video capsule endoscopy, driving a very useful but not fea- sible clinical routine into a feasible clinical procedure. Our proposal is divided into two different parts: The first part tackles the problem of the automatic detection of phasic contractions in capsule endoscopy videos. Phasic contractions are dynamic events spanning about 4-5 seconds, which show visual patterns with a high variability. Our proposal is based on a sequential design which involves the analysis of textural, color and blob features with powerful classifiers such as SVM. This approach appears to cope with two basic aims: the reduction of the imbalance rate of the data set, and the modular construction of the system, which adds the capability of including domain knowledge as new stages in the cascade. The second part of the current work tackles the problem of the automatic detection of tonic contractions. Tonic contrac- tions manifest in capsule endoscopy as a sustained pattern of the folds and wrinkles of the intestine, which may be prolonged for an undetermined span of time. Our proposal is based on the analysis of the wrinkle patterns, presenting a comparative study of diverse features and classification methods, and providing a set of appro- priate descriptors for their characterization. We provide a detailed analysis of the performance achieved by our system both in a qualitative and a quantitative way.
	Address	CVC (UAB)
	Corporate Author				Thesis	Ph.D. thesis
	Publisher		Place of Publication		Editor	Petia Radeva
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue	84-933652-7-0	Edition
	ISSN		ISBN		Medium
	Area	800	Expedition		Conference
	Notes	MV;SIAI			Approved	no
	Call Number	Admin @ si @ Vil2006; IAM @ iam @ Vil2006			Serial	738
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	Author	Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Fernando Azpiroz; Petia Radeva
	Title	Anisotropic Feature Extraction from Endoluminal Images for Detection of Intestinal Contractions			Type	Book Chapter
	Year	2006	Publication	9th International Conference on Medical Image Computing and Computer–Assisted Intervention	Abbreviated Journal
	Volume	4191	Issue		Pages	161–168
	Keywords
	Abstract	Wireless endoscopy is a very recent and at the same time unique technique allowing to visualize and study the occurrence of con- tractions and to analyze the intestine motility. Feature extraction is es- sential for getting efficient patterns to detect contractions in wireless video endoscopy of small intestine. We propose a novel method based on anisotropic image filtering and efficient statistical classification of con- traction features. In particular, we apply the image gradient tensor for mining informative skeletons from the original image and a sequence of descriptors for capturing the characteristic pattern of contractions. Fea- tures extracted from the endoluminal images were evaluated in terms of their discriminatory ability in correct classifying images as either belong- ing to contractions or not. Classification was performed by means of a support vector machine classifier with a radial basis function kernel. Our classification rates gave sensitivity of the order of 90.84% and specificity of the order of 94.43% respectively. These preliminary results highlight the high efficiency of the selected descriptors and support the feasibility of the proposed method in assisting the automatic detection and analysis of contractions.
	Address	Copenhagen (Denmark)
	Corporate Author				Thesis
	Publisher	Springer Verlag	Place of Publication	Berlin Heidelberg	Editor	R. Larsen, M. Nielsen, and J. Sporring
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area	800	Expedition		Conference	MICCAI06
	Notes	MV;OR;MILAB;SIAI			Approved	no
	Call Number	BCNPCL @ bcnpcl @ SVV2006; IAM @ iam @ SVV2006			Serial	725
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	Author	Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
	Title	A Region Segmentation Method for Colonoscopy Images Using a Model of Polyp Appearance			Type	Conference Article
	Year	2011	Publication	5th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	6669	Issue		Pages	134-143
	Keywords	Colonoscopy, Polyp Detection, Region Merging, Region Segmentation.
	Abstract	This work aims at the segmentation of colonoscopy images into a minimum number of informative regions. Our method performs in a way such, if a polyp is present in the image, it will be exclusively and totally contained in a single region. This result can be used in later stages to classify regions as polyp-containing candidates. The output of the algorithm also defines which regions can be considered as non-informative. The algorithm starts with a high number of initial regions and merges them taking into account the model of polyp appearance obtained from available data. The results show that our segmentations of polyp regions are more accurate than state-of-the-art methods.
	Address	Las Palmas de Gran Canaria, June 2011
	Corporate Author	SpringerLink			Thesis
	Publisher		Place of Publication		Editor	Vitrià, Jordi and Sanches, João and Hernández, Mario
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes in Computer Science	Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-642-21256-7	Medium
	Area	800	Expedition		Conference	IbPRIA
	Notes	MV;SIAI			Approved	no
	Call Number	IAM @ iam @ BSV2011c			Serial	1696
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