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	Author	V. Valev; Petia Radeva
	Title	Determining Structural Description by Boolean Formulas.			Type	Book Chapter
	Year	1992	Publication	Advances in Structural and Syntactic Pattern Recognition	Abbreviated Journal
	Volume	5	Issue		Pages	131–140
	Keywords
	Abstract	Pattern recognition is an active area of research with many applications, some of which have reached commercial maturity. Structural and syntactic methods are very powerful. They are based on symbolic data structures together with matching, parsing, and reasoning procedures that are able to infer interpretations of complex input patterns. This book gives an overview of the latest developments and achievements in the field.
	Address
	Corporate Author				Thesis
	Publisher	World Scientific	Place of Publication		Editor	H. Bunke
	Language		Summary Language		Original Title
	Series Editor		Series Title	Machine Perception and Artificial Intelligence:	Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-981-279-791-9	Medium
	Area		Expedition		Conference
	Notes	MILAB			Approved	no
	Call Number	BCNPCL @ bcnpcl @ VaR1992c			Serial	254
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	Author	Oriol Rodriguez-Leor; R. Hemetsberger; Francesco Ciompi; E Fernandez-Nofrerias; Angel Serrano; M. Bernet; Petia Radeva; J. Mauri; A. Bayes
	Title	Caracteritzacio automatica de la placa mitjançant analisis del espectre de radiofreqüencia en estudi de ecografia intracoronaria: resultat de la fusio de dades invivo i exvivo			Type	Conference Article
	Year	2010	Publication	22nd Congres Societat Catalana de Cardiologia,	Abbreviated Journal
	Volume		Issue		Pages	131
	Keywords
	Abstract
	Address	Barcelona (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
	Notes	MILAB			Approved	no
	Call Number	BCNPCL @ bcnpcl @ RHC2010			Serial	1368
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	Author	Henry Velesaca; Patricia Suarez; Dario Carpio; Angel Sappa
	Title	Synthesized Image Datasets: Towards an Annotation-Free Instance Segmentation Strategy			Type	Conference Article
	Year	2021	Publication	16th International Symposium on Visual Computing	Abbreviated Journal
	Volume	13017	Issue		Pages	131–143
	Keywords
	Abstract	This paper presents a complete pipeline to perform deep learning-based instance segmentation of different types of grains (e.g., corn, sunflower, soybeans, lentils, chickpeas, mote, and beans). The proposed approach consists of using synthesized image datasets for the training process, which are easily generated according to the category of the instance to be segmented. The synthesized imaging process allows generating a large set of well-annotated grain samples with high variability—as large and high as the user requires. Instance segmentation is performed through a popular deep learning based approach, the Mask R-CNN architecture, but any learning-based instance segmentation approach can be considered. Results obtained by the proposed pipeline show that the strategy of using synthesized image datasets for training instance segmentation helps to avoid the time-consuming image annotation stage, as well as to achieve higher intersection over union and average precision performances. Results obtained with different varieties of grains are shown, as well as comparisons with manually annotated images, showing both the simplicity of the process and the improvements in the performance.
	Address	Virtual; October 2021
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ISVC
	Notes	MSIAU			Approved	no
	Call Number	Admin @ si @ VSC2021			Serial	3667
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	Author	Oriol Rodriguez-Leor; Debora Gil; Eduard Fernandez-Nofrerias; H. Tizon; S. Montserrat; Vicente del Valle; J. Mauri
	Title	Caracterització de la Perfusió Miocàrdica mitjançant anàlisi estadístic de l espectre en l angiografia de contrast			Type	Conference Article
	Year	2007	Publication	XIX Congrés de la Societat Catalana de Cardiologia de Barcelona	Abbreviated Journal
	Volume		Issue		Pages	130
	Keywords
	Abstract	La valoració de la integritat de la microcirculació coronària aporta informació pronòstica en pacients amb infart agut de miocardi en els que es realitza angioplastia primària. Aquesta valoració és subjectiva i presenta una important variabilitat si no es duta a terme per personal experimentat. Presentem una eina d’anàlisi d’imatge que permet fer una valoració de la microcirculació coronària a partir de seqüències d’angiografia. Hem analitzat les variacions locals en el nivell de gris de la imatge durant la seqüència angiogràfica. Hem identificat els principals fenòmens observats (respiració, batec cardíac, tinció arterial, tinció miocàrdica i soroll radiològic) mitjançant un anàlisi estadístic de l’espectre de Fourier de l’evolució al llarg del temps de la mitja local. Aquest mateix anàlisis permet determinat la influència de cadascun d’ells en la extracció del patró de tinció i selecciona la respiració com el fenomen que més distorsiona el patró de tinció original. Els descriptors proposats s’obtenen fora del rang espectral respiratori. Hem testat la seva capacitat per a detectar els tres fenòmens principals (tinció miocàrdica (MS), tinció arterial (AS) i soroll (NS)) independentment de la respiració. La capacitat de discriminació dels descriptors ha estat valorada mitjançant un mètode de crossvalidation en 30 seqüències d’angiografia. Els descriptors emprats permeten caracteritzar la tinció miocàrdica amb una alta eficiència i fiabilitat. A més no hi ha diferències significatives en l’anàlisi de les seqüències obtingudes amb el pacient respirant amb normalitat o en apnea
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication	Barcelona (Spain)	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	IAM			Approved	no
	Call Number	IAM @ iam @ RGF2007			Serial	1639
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	Author	Victor Ponce; Hugo Jair Escalante; Sergio Escalera; Xavier Baro
	Title	Gesture and Action Recognition by Evolved Dynamic Subgestures			Type	Conference Article
	Year	2015	Publication	26th British Machine Vision Conference	Abbreviated Journal
	Volume		Issue		Pages	129.1-129.13
	Keywords
	Abstract	This paper introduces a framework for gesture and action recognition based on the evolution of temporal gesture primitives, or subgestures. Our work is inspired on the principle of producing genetic variations within a population of gesture subsequences, with the goal of obtaining a set of gesture units that enhance the generalization capability of standard gesture recognition approaches. In our context, gesture primitives are evolved over time using dynamic programming and generative models in order to recognize complex actions. In few generations, the proposed subgesture-based representation of actions and gestures outperforms the state of the art results on the MSRDaily3D and MSRAction3D datasets.
	Address	Swansea; uk; September 2015
	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	BMVC
	Notes	HuPBA;MV			Approved	no
	Call Number	Admin @ si @ PEE2015			Serial	2657
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	Author	Carlo Gatta; Oriol Pujol; Oriol Rodriguez-Leor; J. Mauri; Petia Radeva
	Title	Improved Rigid Registration of Vessel Structures using the Fast Radial Symmetry Transform			Type	Conference Article
	Year	2008	Publication	Computer Vision for Intravascular Imaging CVII’08 Workshop Medical Image Computing and Computer–Assisted Intervention , 11th International Conference	Abbreviated Journal
	Volume		Issue		Pages	128–136
	Keywords
	Abstract
	Address	NY (USA)
	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	MICCAI
	Notes	MILAB;HUPBA			Approved	no
	Call Number	BCNPCL @ bcnpcl @ GPR2008b			Serial	1038
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	Author	Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez
	Title	An Adapted Alternation Approach for Recommender Systems			Type	Conference Article
	Year	2008	Publication	IEEE International Conference on e–Business Engineering,	Abbreviated Journal
	Volume		Issue		Pages	128–135
	Keywords
	Abstract	This paper presents an adaptation of the alternation technique to tackle the prediction task in recommender systems. These systems are widely considered in electronic commerce to help customers to find products they will probably like or dislike. As the SVD-based approaches, the proposed adapted alternation technique uses all the information stored in the system to find the predictions. The main advantage of this technique with respect to the SVD-based ones is that it can deal with missing data. Furthermore, it has a smaller computational cost. Experimental results with public data sets are provided in order to show the viability of the proposed adapted alternation approach.
	Address	Xi’an (Xina)
	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	ADAS			Approved	no
	Call Number	ADAS @ adas @ JSL2008e			Serial	1044
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	Author	Oriol Rodriguez-Leor; Debora Gil; Eduard Fernandez-Nofrerias
	Title	Analisis en los cambios en el nivel de gris en las secuencias angiograficas mediante descriptores estadisticos para determinar la perfusion miocardica			Type	Journal Article
	Year	2006	Publication	Revista Española de Cardiología	Abbreviated Journal	REC
	Volume	59 Supl 2-166	Issue	2	Pages	128
	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	IAM;			Approved	no
	Call Number	IAM @ iam @ RGF2006			Serial	1640
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	Author	Arjan Gijsenij; Theo Gevers; Joost Van de Weijer
	Title	Generalized Gamut Mapping using Image Derivative Structures for Color Constancy			Type	Journal Article
	Year	2010	Publication	International Journal of Computer Vision	Abbreviated Journal	IJCV
	Volume	86	Issue	2-3	Pages	127-139
	Keywords
	Abstract	The gamut mapping algorithm is one of the most promising methods to achieve computational color constancy. However, so far, gamut mapping algorithms are restricted to the use of pixel values to estimate the illuminant. Therefore, in this paper, gamut mapping is extended to incorporate the statistical nature of images. It is analytically shown that the proposed gamut mapping framework is able to include any linear filter output. The main focus is on the local n-jet describing the derivative structure of an image. It is shown that derivatives have the advantage over pixel values to be invariant to disturbing effects (i.e. deviations of the diagonal model) such as saturated colors and diffuse light. Further, as the n-jet based gamut mapping has the ability to use more information than pixel values alone, the combination of these algorithms are more stable than the regular gamut mapping algorithm. Different methods of combining are proposed. Based on theoretical and experimental results conducted on large scale data sets of hyperspectral, laboratory and realworld scenes, it can be derived that (1) in case of deviations of the diagonal model, the derivative-based approach outperforms the pixel-based gamut mapping, (2) state-of-the-art algorithms are outperformed by the n-jet based gamut mapping, (3) the combination of the different n-jet based gamut
	Address
	Corporate Author				Thesis
	Publisher	Kluwer Academic Publishers Hingham, MA, USA	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0920-5691	ISBN		Medium
	Area		Expedition		Conference
	Notes	ISE			Approved	no
	Call Number	CAT @ cat @ GGW2010			Serial	1274
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	Author	Joana Maria Pujadas-Mora; Alicia Fornes; Josep Llados; Anna Cabre
	Title	Bridging the gap between historical demography and computing: tools for computer-assisted transcription and the analysis of demographic sources			Type	Book Chapter
	Year	2016	Publication	The future of historical demography. Upside down and inside out	Abbreviated Journal
	Volume		Issue		Pages	127-131
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher	Acco Publishers	Place of Publication		Editor	K.Matthijs; S.Hin; H.Matsuo; J.Kok
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-94-6292-722-3	Medium
	Area		Expedition		Conference
	Notes	DAG; 600.097			Approved	no
	Call Number	Admin @ si @ PFL2016			Serial	2907
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	Author	B. Gautam; Oriol Ramos Terrades; Joana Maria Pujadas-Mora; Miquel Valls-Figols
	Title	Knowledge graph based methods for record linkage			Type	Journal Article
	Year	2020	Publication	Pattern Recognition Letters	Abbreviated Journal	PRL
	Volume	136	Issue		Pages	127-133
	Keywords
	Abstract	Nowadays, it is common in Historical Demography the use of individual-level data as a consequence of a predominant life-course approach for the understanding of the demographic behaviour, family transition, mobility, etc. Advanced record linkage is key since it allows increasing the data complexity and its volume to be analyzed. However, current methods are constrained to link data from the same kind of sources. Knowledge graph are flexible semantic representations, which allow to encode data variability and semantic relations in a structured manner. In this paper we propose the use of knowledge graph methods to tackle record linkage tasks. The proposed method, named WERL, takes advantage of the main knowledge graph properties and learns embedding vectors to encode census information. These embeddings are properly weighted to maximize the record linkage performance. We have evaluated this method on benchmark data sets and we have compared it to related methods with stimulating and satisfactory results.
	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; 600.140; 600.121			Approved	no
	Call Number	Admin @ si @ GRP2020			Serial	3453
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	Author	Razieh Rastgoo; Kourosh Kiani; Sergio Escalera
	Title	Hand pose aware multimodal isolated sign language recognition			Type	Journal Article
	Year	2020	Publication	Multimedia Tools and Applications	Abbreviated Journal	MTAP
	Volume	80	Issue		Pages	127–163
	Keywords
	Abstract	Isolated hand sign language recognition from video is a challenging research area in computer vision. Some of the most important challenges in this area include dealing with hand occlusion, fast hand movement, illumination changes, or background complexity. While most of the state-of-the-art results in the field have been achieved using deep learning-based models, the previous challenges are not completely solved. In this paper, we propose a hand pose aware model for isolated hand sign language recognition using deep learning approaches from two input modalities, RGB and depth videos. Four spatial feature types: pixel-level, flow, deep hand, and hand pose features, fused from both visual modalities, are input to LSTM for temporal sign recognition. While we use Optical Flow (OF) for flow information in RGB video inputs, Scene Flow (SF) is used for depth video inputs. By including hand pose features, we show a consistent performance improvement of the sign language recognition model. To the best of our knowledge, this is the first time that this discriminant spatiotemporal features, benefiting from the hand pose estimation features and multi-modal inputs, are fused for isolated hand sign language recognition. We perform a step-by-step analysis of the impact in terms of recognition performance of the hand pose features, different combinations of the spatial features, and different recurrent models, especially LSTM and GRU. Results on four public datasets confirm that the proposed model outperforms the current state-of-the-art models on Montalbano II, MSR Daily Activity 3D, and CAD-60 datasets with a relative accuracy improvement of 1.64%, 6.5%, and 7.6%. Furthermore, our model obtains a competitive results on isoGD dataset with only 0.22% margin lower than the current state-of-the-art model.
	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 menciona			Approved	no
	Call Number	Admin @ si @ RKE2020			Serial	3524
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	Author	Marina Alberti; Carlo Gatta; Simone Balocco; Francesco Ciompi; Oriol Pujol; Joana Silva; Xavier Carrillo; Petia Radeva
	Title	Automatic Branching Detection in IVUS Sequences			Type	Conference Article
	Year	2011	Publication	5th Iberian Conference on Pattern Recognition and Image Analysis	Abbreviated Journal
	Volume	6669	Issue		Pages	126-133
	Keywords
	Abstract	Atherosclerosis is a vascular pathology affecting the arterial walls, generally located in specific vessel sites, such as bifurcations. In this paper, for the first time, a fully automatic approach for the detection of bifurcations in IVUS pullback sequences is presented. The method identifies the frames and the angular sectors in which a bifurcation is visible. This goal is achieved by applying a classifier to a set of textural features extracted from each image of an IVUS pullback. A comparison between two state-of-the-art classifiers is performed, AdaBoost and Random Forest. A cross-validation scheme is applied in order to evaluate the performances of the approaches. The obtained results are encouraging, showing a sensitivity of 75% and an accuracy of 94% by using the AdaBoost algorithm.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication	Berlin	Editor	Jordi Vitria; Joao Miguel Raposo; Mario Hernandez
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-21256-7	Medium
	Area		Expedition		Conference	IbPRIA
	Notes	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ AGB2011			Serial	1740
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	Author	Miguel Angel Bautista; Antonio Hernandez; Victor Ponce; Xavier Perez Sala; Xavier Baro; Oriol Pujol; Cecilio Angulo; Sergio Escalera
	Title	Probability-based Dynamic TimeWarping for Gesture Recognition on RGB-D data			Type	Conference Article
	Year	2012	Publication	21st International Conference on Pattern Recognition International Workshop on Depth Image Analysis	Abbreviated Journal
	Volume	7854	Issue		Pages	126-135
	Keywords
	Abstract	Dynamic Time Warping (DTW) is commonly used in gesture recognition tasks in order to tackle the temporal length variability of gestures. In the DTW framework, a set of gesture patterns are compared one by one to a maybe infinite test sequence, and a query gesture category is recognized if a warping cost below a certain threshold is found within the test sequence. Nevertheless, either taking one single sample per gesture category or a set of isolated samples may not encode the variability of such gesture category. In this paper, a probability-based DTW for gesture recognition is proposed. Different samples of the same gesture pattern obtained from RGB-Depth data are used to build a Gaussian-based probabilistic model of the gesture. Finally, the cost of DTW has been adapted accordingly to the new model. The proposed approach is tested in a challenging scenario, showing better performance of the probability-based DTW in comparison to state-of-the-art approaches for gesture recognition on RGB-D data.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-40302-6	Medium
	Area		Expedition		Conference	WDIA
	Notes	MILAB; OR;HuPBA;MV			Approved	no
	Call Number	Admin @ si @ BHP2012			Serial	2120
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	Author	Mariella Dimiccoli; Benoît Girard; Alain Berthoz; Daniel Bennequin
	Title	Striola Magica: a functional explanation of otolith organs			Type	Journal Article
	Year	2013	Publication	Journal of Computational Neuroscience	Abbreviated Journal	JCN
	Volume	35	Issue	2	Pages	125-154
	Keywords	Otolith organs ;Striola; Vestibular pathway
	Abstract	Otolith end organs of vertebrates sense linear accelerations of the head and gravitation. The hair cells on their epithelia are responsible for transduction. In mammals, the striola, parallel to the line where hair cells reverse their polarization, is a narrow region centered on a curve with curvature and torsion. It has been shown that the striolar region is functionally different from the rest, being involved in a phasic vestibular pathway. We propose a mathematical and computational model that explains the necessity of this amazing geometry for the striola to be able to carry out its function. Our hypothesis, related to the biophysics of the hair cells and to the physiology of their afferent neurons, is that striolar afferents collect information from several type I hair cells to detect the jerk in a large domain of acceleration directions. This predicts a mean number of two calyces for afferent neurons, as measured in rodents. The domain of acceleration directions sensed by our striolar model is compatible with the experimental results obtained on monkeys considering all afferents. Therefore, the main result of our study is that phasic and tonic vestibular afferents cover the same geometrical fields, but at different dynamical and frequency domains.
	Address
	Corporate Author				Thesis
	Publisher	Springer US	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1573-6873. 2013	ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @DBG2013			Serial	2787
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