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	Author	Claudio Baecchi; Francesco Turchini; Lorenzo Seidenari; Andrew Bagdanov; Alberto del Bimbo
	Title	Fisher vectors over random density forest for object recognition			Type	Conference Article
	Year	2014	Publication	22nd International Conference on Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages	4328-4333
	Keywords
	Abstract
	Address	Stockholm; Sweden; August 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		Medium
	Area		Expedition		Conference	ICPR
	Notes	LAMP; 600.079			Approved	no
	Call Number	Admin @ si @ BTS2014			Serial	2518
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	Author	Clement Guerin; Christophe Rigaud; Karell Bertet; Jean-Christophe Burie; Arnaud Revel ; Jean-Marc Ogier
	Title	Réduction de l’espace de recherche pour les personnages de bandes dessinées			Type	Conference Article
	Year	2014	Publication	19th National Congress Reconnaissance de Formes et l'Intelligence Artificielle	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	contextual search; document analysis; comics characters
	Abstract	Les bandes dessinées représentent un patrimoine culturel important dans de nombreux pays et leur numérisation massive offre la possibilité d'effectuer des recherches dans le contenu des images. À ce jour, ce sont principalement les structures des pages et leurs contenus textuels qui ont été étudiés, peu de travaux portent sur le contenu graphique. Nous proposons de nous appuyer sur des éléments déjà étudiés tels que la position des cases et des bulles, pour réduire l'espace de recherche et localiser les personnages en fonction de la queue des bulles. L'évaluation de nos différentes contributions à partir de la base eBDtheque montre un taux de détection des queues de bulle de 81.2%, de localisation des personnages allant jusqu'à 85% et un gain d'espace de recherche de plus de 50%.
	Address	Rouen; Francia; July 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		Medium
	Area		Expedition		Conference	RFIA
	Notes	DAG; 600.077			Approved	no
	Call Number	Admin @ si @ GRB2014			Serial	2480
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	Author	Clementine Decamps; Alexis Arnaud; Florent Petitprez; Mira Ayadi; Aurelia Baures; Lucile Armenoult; Sergio Escalera; Isabelle Guyon; Remy Nicolle; Richard Tomasini; Aurelien de Reynies; Jerome Cros; Yuna Blum; Magali Richard
	Title	DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification			Type	Journal Article
	Year	2021	Publication	BMC Bioinformatics	Abbreviated Journal
	Volume	22	Issue		Pages	473
	Keywords
	Abstract	Quantification of tumor heterogeneity is essential to better understand cancer progression and to adapt therapeutic treatments to patient specificities. Bioinformatic tools to assess the different cell populations from single-omic datasets as bulk transcriptome or methylome samples have been recently developed, including reference-based and reference-free methods. Improved methods using multi-omic datasets are yet to be developed in the future and the community would need systematic tools to perform a comparative evaluation of these algorithms on controlled data.
	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 @ DAP2021			Serial	3650
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	Author	Corina Krauter; Ursula Reiter; Albrecht Schmidt; Marc Masana; Rudolf Stollberger; Michael Fuchsjager; Gert Reiter
	Title	Objective extraction of the temporal evolution of the mitral valve vortex ring from 4D flow MRI			Type	Conference Article
	Year	2019	Publication	27th Annual Meeting & Exhibition of the International Society for Magnetic Resonance in Medicine	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	The mitral valve vortex ring is a promising flow structure for analysis of diastolic function, however, methods for objective extraction of its formation to dissolution are lacking. We present a novel algorithm for objective extraction of the temporal evolution of the mitral valve vortex ring from magnetic resonance 4D flow data and validated the method against visual analysis. The algorithm successfully extracted mitral valve vortex rings during both early- and late-diastolic filling and agreed substantially with visual assessment. Early-diastolic mitral valve vortex ring properties differed between healthy subjects and patients with ischemic heart disease.
	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	ISMRM
	Notes	LAMP; 600.120			Approved	no
	Call Number	Admin @ si @ KRS2019			Serial	3300
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	Author	Craig Von Land; Ricardo Toledo; Juan J. Villanueva
	Title	TeleRegions: Application of Telematics in Cardiac Care.			Type	Miscellaneous
	Year	1997	Publication	Computers in Cardiology, 1997. Piscataway, NJ: IEEE Computer Society Press, 24: 645–8.	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	ADAS			Approved	no
	Call Number	ISE @ ise @ VTV1997			Serial	64
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	Author	Craig Von Land; Ricardo Toledo; Juan J. Villanueva
	Title	TeleRegion: Tele-Applications for European Regions			Type	Miscellaneous
	Year	1996	Publication	Experiencias de validacion, uso y expansion de la telematica a nivel regional e inter–regional. Convencion Iberoamericana sobre la Salud en la Sociedad Global de la Informacion.	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Buenos Aires, Argentina
	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	ISE @ ise @ VTV1996b			Serial	101
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	Author	Craig Von Land; Ricardo Toledo; Juan J. Villanueva
	Title	Object Oriented Design of the DICOM standard			Type	Miscellaneous
	Year	1996	Publication	International Symposium on Cardiovascular Imaging.	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Leiden, The Netherlands
	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	ISE @ ise @ VTV1996c			Serial	104
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	Author	Craig Von Land; Ricardo Toledo; Juan J. Villanueva
	Title	CARE: Computer Assisted Radiology Environment			Type	Miscellaneous
	Year	1996	Publication	Tecnologia de Imagenes Medicas, Convencion Iberoamericana sobre la Salud en la Sociedad Global de la Informacion.	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Buenos Aires, Argentina
	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	ISE @ ise @ VTV1996a			Serial	99
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	Author	Craig Von Land; V. Lashin; A. Oriol; Juan J. Villanueva
	Title	Object-oriented Design of the DICOM Standard and its Application to Cardiovascular Imaging.			Type	Miscellaneous
	Year	1997	Publication	Computers in Cardiology 1997. Piscataway, NJ: IEEE Computer Society Press,24: 645–8.	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				Approved	no
	Call Number	ISE @ ise @ VLO1997			Serial	68
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	Author	Cristhian A. Aguilera-Carrasco
	Title	Evaluation of feature detectors and descriptors in VISIBLE-LWIR cross-spectral imaging			Type	Report
	Year	2014	Publication	CVC Technical Report	Abbreviated Journal
	Volume	177	Issue		Pages
	Keywords	Multi-spectral; Cross-spectral; Visible-LWIR imaging; Multimodal.
	Abstract	This thesis evaluates the performance of different state-of-art feature detectors and descriptors algorithms in the Visible-LWIR cross-spectral scenario. The focus is to determine if current detector and descriptor algorithms can be used to match features between the LWIR spectrum and the visible spectrum in applications such as, visual odometry, object recognition, image registration and stereo vision. An outdoor cross-spectral dataset was created to evaluate the suitability of the different algorithms. The results show that the tested algorithms are not suitable to the task of matching features across different spectra. The repeatability ratio was smaller than the 30 percent in the best case and in general matched features were not accurate located. Additionally, these results also suggest that is necessary to create new algorithms that take into account the nature of the different spectra, describing characteristics that exist in both spectra such as discontinuities.
	Address
	Corporate Author				Thesis	Master's 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; 600.076			Approved	no
	Call Number	Admin @ si @Agu2014			Serial	2526
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	Author	Cristhian A. Aguilera-Carrasco; Angel Sappa; Cristhian Aguilera; Ricardo Toledo
	Title	Cross-Spectral Local Descriptors via Quadruplet Network			Type	Journal Article
	Year	2017	Publication	Sensors	Abbreviated Journal	SENS
	Volume	17	Issue	4	Pages	873
	Keywords
	Abstract	This paper presents a novel CNN-based architecture, referred to as Q-Net, to learn local feature descriptors that are useful for matching image patches from two different spectral bands. Given correctly matched and non-matching cross-spectral image pairs, a quadruplet network is trained to map input image patches to a common Euclidean space, regardless of the input spectral band. Our approach is inspired by the recent success of triplet networks in the visible spectrum, but adapted for cross-spectral scenarios, where, for each matching pair, there are always two possible non-matching patches: one for each spectrum. Experimental evaluations on a public cross-spectral VIS-NIR dataset shows that the proposed approach improves the state-of-the-art. Moreover, the proposed technique can also be used in mono-spectral settings, obtaining a similar performance to triplet network descriptors, but requiring less training data.
	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	ADAS; 600.086; 600.118			Approved	no
	Call Number	Admin @ si @ ASA2017			Serial	2914
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	Author	Cristhian A. Aguilera-Carrasco; Angel Sappa; Ricardo Toledo
	Title	LGHD: a Feature Descriptor for Matching Across Non-Linear Intensity Variations			Type	Conference Article
	Year	2015	Publication	22th IEEE International Conference on Image Processing	Abbreviated Journal
	Volume		Issue		Pages	178 - 181
	Keywords
	Abstract
	Address	Quebec; Canada; 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	ICIP
	Notes	ADAS; 600.076			Approved	no
	Call Number	Admin @ si @ AST2015			Serial	2630
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	Author	Cristhian A. Aguilera-Carrasco; C. Aguilera; Angel Sappa
	Title	Melamine Faced Panels Defect Classification beyond the Visible Spectrum			Type	Journal Article
	Year	2018	Publication	Sensors	Abbreviated Journal	SENS
	Volume	18	Issue	11	Pages	1-10
	Keywords	industrial application; infrared; machine learning
	Abstract	In this work, we explore the use of images from different spectral bands to classify defects in melamine faced panels, which could appear through the production process. Through experimental evaluation, we evaluate the use of images from the visible (VS), near-infrared (NIR), and long wavelength infrared (LWIR), to classify the defects using a feature descriptor learning approach together with a support vector machine classifier. Two descriptors were evaluated, Extended Local Binary Patterns (E-LBP) and SURF using a Bag of Words (BoW) representation. The evaluation was carried on with an image set obtained during this work, which contained five different defect categories that currently occurs in the industry. Results show that using images from beyond the visual spectrum helps to improve classification performance in contrast with a single visible spectrum solution.
	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	MSIAU; 600.122			Approved	no
	Call Number	Admin @ si @ AAS2018			Serial	3191
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	Author	Cristhian A. Aguilera-Carrasco; Cristhian Aguilera; Cristobal A. Navarro; Angel Sappa
	Title	Fast CNN Stereo Depth Estimation through Embedded GPU Devices			Type	Journal Article
	Year	2020	Publication	Sensors	Abbreviated Journal	SENS
	Volume	20	Issue	11	Pages	3249
	Keywords	stereo matching; deep learning; embedded GPU
	Abstract	Current CNN-based stereo depth estimation models can barely run under real-time constraints on embedded graphic processing unit (GPU) devices. Moreover, state-of-the-art evaluations usually do not consider model optimization techniques, being that it is unknown what is the current potential on embedded GPU devices. In this work, we evaluate two state-of-the-art models on three different embedded GPU devices, with and without optimization methods, presenting performance results that illustrate the actual capabilities of embedded GPU devices for stereo depth estimation. More importantly, based on our evaluation, we propose the use of a U-Net like architecture for postprocessing the cost-volume, instead of a typical sequence of 3D convolutions, drastically augmenting the runtime speed of current models. In our experiments, we achieve real-time inference speed, in the range of 5–32 ms, for 1216 × 368 input stereo images on the Jetson TX2, Jetson Xavier, and Jetson Nano embedded devices.
	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	MSIAU; 600.122			Approved	no
	Call Number	Admin @ si @ AAN2020			Serial	3428
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	Author	Cristhian A. Aguilera-Carrasco; F. Aguilera; Angel Sappa; C. Aguilera; Ricardo Toledo
	Title	Learning cross-spectral similarity measures with deep convolutional neural networks			Type	Conference Article
	Year	2016	Publication	29th IEEE Conference on Computer Vision and Pattern Recognition Worshops	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	The simultaneous use of images from different spectracan be helpful to improve the performance of many computer vision tasks. The core idea behind the usage of crossspectral approaches is to take advantage of the strengths of each spectral band providing a richer representation of a scene, which cannot be obtained with just images from one spectral band. In this work we tackle the cross-spectral image similarity problem by using Convolutional Neural Networks (CNNs). We explore three different CNN architectures to compare the similarity of cross-spectral image patches. Specifically, we train each network with images from the visible and the near-infrared spectrum, and then test the result with two public cross-spectral datasets. Experimental results show that CNN approaches outperform the current state-of-art on both cross-spectral datasets. Additionally, our experiments show that some CNN architectures are capable of generalizing between different crossspectral domains.
	Address	Las vegas; USA; June 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	CVPRW
	Notes	ADAS; 600.086; 600.076			Approved	no
	Call Number	Admin @ si @AAS2016			Serial	2809
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