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	Author	Mohamed Ali Souibgui; Asma Bensalah; Jialuo Chen; Alicia Fornes; Michelle Waldispühl
	Title	A User Perspective on HTR methods for the Automatic Transcription of Rare Scripts: The Case of Codex Runicus Just Accepted			Type	Journal Article
	Year	2023	Publication	ACM Journal on Computing and Cultural Heritage	Abbreviated Journal	JOCCH
	Volume	15	Issue	4	Pages	1-18
	Keywords
	Abstract	Recent breakthroughs in Artificial Intelligence, Deep Learning and Document Image Analysis and Recognition have significantly eased the creation of digital libraries and the transcription of historical documents. However, for documents in rare scripts with few labelled training data available, current Handwritten Text Recognition (HTR) systems are too constraint. Moreover, research on HTR often focuses on technical aspects only, and rarely puts emphasis on implementing software tools for scholars in Humanities. In this article, we describe, compare and analyse different transcription methods for rare scripts. We evaluate their performance in a real use case of a medieval manuscript written in the runic script (Codex Runicus) and discuss advantages and disadvantages of each method from the user perspective. From this exhaustive analysis and comparison with a fully manual transcription, we raise conclusions and provide recommendations to scholars interested in using automatic transcription tools.
	Address
	Corporate Author				Thesis
	Publisher	ACM	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; 600.121; 600.162; 602.230; 600.140			Approved	no
	Call Number	Admin @ si @ SBC2023			Serial	3732
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	Author	Debora Gil; Agnes Borras; Sergio Vera; Miguel Angel Gonzalez Ballester
	Title	A Validation Benchmark for Assessment of Medial Surface Quality for Medical Applications			Type	Conference Article
	Year	2013	Publication	9th International Conference on Computer Vision Systems	Abbreviated Journal
	Volume	7963	Issue		Pages	334-343
	Keywords	Medial Surfaces; Shape Representation; Medical Applications; Performance Evaluation
	Abstract	Confident use of medial surfaces in medical decision support systems requires evaluating their quality for detecting pathological deformations and describing anatomical volumes. Validation in the medical imaging field is a challenging task mainly due to the difficulties for getting consensual ground truth. In this paper we propose a validation benchmark for assessing medial surfaces in the context of medical applications. Our benchmark includes a home-made database of synthetic medial surfaces and volumes and specific scores for evaluating surface accuracy, its stability against volume deformations and its capabilities for accurate reconstruction of anatomical volumes.
	Address	Sant Petersburg; Russia; July 2013
	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	978-3-642-39401-0	Medium
	Area		Expedition		Conference	ICVS
	Notes	IAM; 600.044; 600.060			Approved	no
	Call Number	Admin @ si @ GBV2013			Serial	2300
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	Author	Aura Hernandez-Sabate; Monica Mitiko; Sergio Shiguemi; Debora Gil
	Title	A validation protocol for assessing cardiac phase retrieval in IntraVascular UltraSound			Type	Conference Article
	Year	2010	Publication	Computing in Cardiology	Abbreviated Journal
	Volume	37	Issue		Pages	899-902
	Keywords
	Abstract	A good reliable approach to cardiac triggering is of utmost importance in obtaining accurate quantitative results of atherosclerotic plaque burden from the analysis of IntraVascular UltraSound. Although, in the last years, there has been an increase in research of methods for retrospective gating, there is no general consensus in a validation protocol. Many methods are based on quality assessment of longitudinal cuts appearance and those reporting quantitative numbers do not follow a standard protocol. Such heterogeneity in validation protocols makes faithful comparison across methods a difficult task. We propose a validation protocol based on the variability of the retrieved cardiac phase and explore the capability of several quality measures for quantifying such variability. An ideal detector, suitable for its application in clinical practice, should produce stable phases. That is, it should always sample the same cardiac cycle fraction. In this context, one should measure the variability (variance) of a candidate sampling with respect a ground truth (reference) sampling, since the variance would indicate how spread we are aiming a target. In order to quantify the deviation between the sampling and the ground truth, we have considered two quality scores reported in the literature: signed distance to the closest reference sample and distance to the right of each reference sample. We have also considered the residuals of the regression line of reference against candidate sampling. The performance of the measures has been explored on a set of synthetic samplings covering different cardiac cycle fractions and variabilities. From our simulations, we conclude that the metrics related to distances are sensitive to the shift considered while the residuals are robust against fraction and variabilities as far as one can establish a pair-wise correspondence between candidate and reference. We will further investigate the impact of false positive and negative detections in experimental data.
	Address
	Corporate Author				Thesis
	Publisher	IEEE	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0276-6547	ISBN	978-1-4244-7318-2	Medium
	Area		Expedition		Conference	CINC
	Notes	IAM;			Approved	no
	Call Number	IAM @ iam @ HSM2010			Serial	1551
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	Author	Jaume Garcia; Debora Gil; Sandra Pujades; Francesc Carreras
	Title	A Variational Framework for Assessment of the Left Ventricle Motion			Type	Journal Article
	Year	2008	Publication	International Journal Mathematical Modelling of Natural Phenomena	Abbreviated Journal
	Volume	3	Issue	6	Pages	76-100
	Keywords	Key words: Left Ventricle Dynamics, Ventricular Torsion, Tagged Magnetic Resonance, Motion Tracking, Variational Framework, Gabor Transform.
	Abstract	Impairment of left ventricular contractility due to cardiovascular diseases is reflected in left ventricle (LV) motion patterns. An abnormal change of torsion or long axis shortening LV values can help with the diagnosis and follow-up of LV dysfunction. Tagged Magnetic Resonance (TMR) is a widely spread medical imaging modality that allows estimation of the myocardial tissue local deformation. In this work, we introduce a novel variational framework for extracting the left ventricle dynamics from TMR sequences. A bi-dimensional representation space of TMR images given by Gabor filter banks is defined. Tracking of the phases of the Gabor response is combined using a variational framework which regularizes the deformation field just at areas where the Gabor amplitude drops, while restoring the underlying motion otherwise. The clinical applicability of the proposed method is illustrated by extracting normality models of the ventricular torsion from 19 healthy subjects.
	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 @ GGC2008a			Serial	1058
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	Author	J. Nuñez; O. Fors; Xavier Otazu; Vicenç Pala; Roman Arbiol; M.T. Merino
	Title	A Wavelet-Based Method for the Determination of the Relative Resolution Between Remotely Sensed Images			Type	Journal
	Year	2006	Publication	IEEE Transactions on Geoscience and Remote Sensing, 44(9): 2539–2548	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	CIC			Approved	no
	Call Number	CAT @ cat @ NFO2006			Serial	660
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	Author	Jialuo Chen; M.A.Souibgui; Alicia Fornes; Beata Megyesi
	Title	A Web-based Interactive Transcription Tool for Encrypted Manuscripts			Type	Conference Article
	Year	2020	Publication	3rd International Conference on Historical Cryptology	Abbreviated Journal
	Volume		Issue		Pages	52-59
	Keywords
	Abstract	Manual transcription of handwritten text is a time consuming task. In the case of encrypted manuscripts, the recognition is even more complex due to the huge variety of alphabets and symbol sets. To speed up and ease this process, we present a web-based tool aimed to (semi)-automatically transcribe the encrypted sources. The user uploads one or several images of the desired encrypted document(s) as input, and the system returns the transcription(s). This process is carried out in an interactive fashion with the user to obtain more accurate results. For discovering and testing, the developed web tool is freely available.
	Address	Virtual; June 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	HistoCrypt
	Notes	DAG; 600.140; 602.230; 600.121			Approved	no
	Call Number	Admin @ si @ CSF2020			Serial	3447
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	Author	Enric Marti; Antoni Gurgui; Debora Gil; Aura Hernandez-Sabate; Jaume Rocarias; Ferran Poveda
	Title	ABP on line: Seguimiento, estregas y evaluación en aprendizaje basado en proyectos			Type	Miscellaneous
	Year	2014	Publication	8th International Congress on University Teaching and Innovation	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Tarragona; juliol 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	CIDUI
	Notes	IAM; ADAS; 600.076; 600.063; 600.075			Approved	no
	Call Number	Admin @ si @ MGG2014			Serial	2457
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	Author	Kai Wang; Joost Van de Weijer; Luis Herranz
	Title	ACAE-REMIND for online continual learning with compressed feature replay			Type	Journal Article
	Year	2021	Publication	Pattern Recognition Letters	Abbreviated Journal	PRL
	Volume	150	Issue		Pages	122-129
	Keywords	online continual learning; autoencoders; vector quantization
	Abstract	Online continual learning aims to learn from a non-IID stream of data from a number of different tasks, where the learner is only allowed to consider data once. Methods are typically allowed to use a limited buffer to store some of the images in the stream. Recently, it was found that feature replay, where an intermediate layer representation of the image is stored (or generated) leads to superior results than image replay, while requiring less memory. Quantized exemplars can further reduce the memory usage. However, a drawback of these methods is that they use a fixed (or very intransigent) backbone network. This significantly limits the learning of representations that can discriminate between all tasks. To address this problem, we propose an auxiliary classifier auto-encoder (ACAE) module for feature replay at intermediate layers with high compression rates. The reduced memory footprint per image allows us to save more exemplars for replay. In our experiments, we conduct task-agnostic evaluation under online continual learning setting and get state-of-the-art performance on ImageNet-Subset, CIFAR100 and CIFAR10 dataset.
	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	LAMP; 600.147; 601.379; 600.120; 600.141			Approved	no
	Call Number	Admin @ si @ WWH2021			Serial	3575
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	Author	Sergi Garcia Bordils; Dimosthenis Karatzas; Marçal Rusiñol
	Title	Accelerating Transformer-Based Scene Text Detection and Recognition via Token Pruning			Type	Conference Article
	Year	2023	Publication	17th International Conference on Document Analysis and Recognition	Abbreviated Journal
	Volume	14192	Issue		Pages	106-121
	Keywords	Scene Text Detection; Scene Text Recognition; Transformer Acceleration
	Abstract	Scene text detection and recognition is a crucial task in computer vision with numerous real-world applications. Transformer-based approaches are behind all current state-of-the-art models and have achieved excellent performance. However, the computational requirements of the transformer architecture makes training these methods slow and resource heavy. In this paper, we introduce a new token pruning strategy that significantly decreases training and inference times without sacrificing performance, striking a balance between accuracy and speed. We have applied this pruning technique to our own end-to-end transformer-based scene text understanding architecture. Our method uses a separate detection branch to guide the pruning of uninformative image features, which significantly reduces the number of tokens at the input of the transformer. Experimental results show how our network is able to obtain competitive results on multiple public benchmarks while running at significantly higher speeds.
	Address	San Jose; CA; USA; August 2023
	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	ICDAR
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ GKR2023a			Serial	3907
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	Author	Andres Traumann; Gholamreza Anbarjafari; Sergio Escalera
	Title	Accurate 3D Measurement Using Optical Depth Information			Type	Journal Article
	Year	2015	Publication	Electronic Letters	Abbreviated Journal	EL
	Volume	51	Issue	18	Pages	1420-1422
	Keywords
	Abstract	A novel three-dimensional measurement technique is proposed. The methodology consists in mapping from the screen coordinates reported by the optical camera to the real world, and integrating distance gradients from the beginning to the end point, while also minimising the error through fitting pixel locations to a smooth curve. The results demonstrate accuracy of less than half a centimetre using Microsoft Kinect II.
	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;MILAB			Approved	no
	Call Number	Admin @ si @ TAE2015			Serial	2647
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	Author	Antonio Hernandez; Carlo Gatta; Sergio Escalera; Laura Igual; Victoria Martin Yuste; Petia Radeva
	Title	Accurate and Robust Fully-Automatic QCA: Method and Numerical Validation			Type	Conference Article
	Year	2011	Publication	14th International Conference on Medical Image Computing and Computer Assisted Intervention	Abbreviated Journal
	Volume	14	Issue	3	Pages	496-503
	Keywords
	Abstract	The Quantitative Coronary Angiography (QCA) is a methodology used to evaluate the arterial diseases and, in particular, the degree of stenosis. In this paper we propose AQCA, a fully automatic method for vessel segmentation based on graph cut theory. Vesselness, geodesic paths and a new multi-scale edgeness map are used to compute a globally optimal artery segmentation. We evaluate the method performance in a rigorous numerical way on two datasets. The method can detect an artery with precision 92.9 +/- 5% and sensitivity 94.2 +/- 6%. The average absolute distance error between detected and ground truth centerline is 1.13 +/- 0.11 pixels (about 0.27 +/- 0.025 mm) and the absolute relative error in the vessel caliber estimation is 2.93% with almost no bias. Moreover, the method can discriminate between arteries and catheter with an accuracy of 96.4%.
	Address	Toronto, Canada
	Corporate Author				Thesis
	Publisher	Springer	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-642-23625-9	Medium
	Area		Expedition		Conference	MICCAI
	Notes	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ HGE2011			Serial	1769
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	Author	Antonio Hernandez; Carlo Gatta; Sergio Escalera; Laura Igual; Victoria Martin-Yuste; Manel Sabate; Petia Radeva
	Title	Accurate coronary centerline extraction, caliber estimation and catheter detection in angiographies			Type	Journal Article
	Year	2012	Publication	IEEE Transactions on Information Technology in Biomedicine	Abbreviated Journal	TITB
	Volume	16	Issue	6	Pages	1332-1340
	Keywords
	Abstract	Segmentation of coronary arteries in X-Ray angiography is a fundamental tool to evaluate arterial diseases and choose proper coronary treatment. The accurate segmentation of coronary arteries has become an important topic for the registration of different modalities which allows physicians rapid access to different medical imaging information from Computed Tomography (CT) scans or Magnetic Resonance Imaging (MRI). In this paper, we propose an accurate fully automatic algorithm based on Graph-cuts for vessel centerline extraction, caliber estimation, and catheter detection. Vesselness, geodesic paths, and a new multi-scale edgeness map are combined to customize the Graph-cuts approach to the segmentation of tubular structures, by means of a global optimization of the Graph-cuts energy function. Moreover, a novel supervised learning methodology that integrates local and contextual information is proposed for automatic catheter detection. We evaluate the method performance on three datasets coming from different imaging systems. The method performs as good as the expert observer w.r.t. centerline detection and caliber estimation. Moreover, the method discriminates between arteries and catheter with an accuracy of 96.5%, sensitivity of 72%, and precision of 97.4%.
	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	1089-7771	ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ HGE2012			Serial	2141
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	Author	R. Valenti; Theo Gevers
	Title	Accurate Eye Center Location through Invariant Isocentric Patterns			Type	Journal Article
	Year	2012	Publication	IEEE Transaction on Pattern Analysis and Machine Intelligence	Abbreviated Journal	TPAMI
	Volume	34	Issue	9	Pages	1785-1798
	Keywords
	Abstract	Impact factor 2010: 5.308 Impact factor 2011/12?: 5.96 Locating the center of the eyes allows for valuable information to be captured and used in a wide range of applications. Accurate eye center location can be determined using commercial eye-gaze trackers, but additional constraints and expensive hardware make these existing solutions unattractive and impossible to use on standard (i.e., visible wavelength), low-resolution images of eyes. Systems based solely on appearance are proposed in the literature, but their accuracy does not allow us to accurately locate and distinguish eye centers movements in these low-resolution settings. Our aim is to bridge this gap by locating the center of the eye within the area of the pupil on low-resolution images taken from a webcam or a similar device. The proposed method makes use of isophote properties to gain invariance to linear lighting changes (contrast and brightness), to achieve in-plane rotational invariance, and to keep low-computational costs. To further gain scale invariance, the approach is applied to a scale space pyramid. In this paper, we extensively test our approach for its robustness to changes in illumination, head pose, scale, occlusion, and eye rotation. We demonstrate that our system can achieve a significant improvement in accuracy over state-of-the-art techniques for eye center location in standard low-resolution imagery.
	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	0162-8828	ISBN		Medium
	Area		Expedition		Conference
	Notes	ALTRES;ISE			Approved	no
	Call Number	Admin @ si @ VaG 2012a			Serial	1849
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	Author	C. Alejandro Parraga; Ramon Baldrich; Maria Vanrell
	Title	Accurate Mapping of Natural Scenes Radiance to Cone Activation Space: A New Image Dataset			Type	Conference Article
	Year	2010	Publication	5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science	Abbreviated Journal
	Volume		Issue		Pages	50–57
	Keywords
	Abstract	The characterization of trichromatic cameras is usually done in terms of a device-independent color space, such as the CIE 1931 XYZ space. This is indeed convenient since it allows the testing of results against colorimetric measures. We have characterized our camera to represent human cone activation by mapping the camera sensor's (RGB) responses to human (LMS) through a polynomial transformation, which can be “customized” according to the types of scenes we want to represent. Here we present a method to test the accuracy of the camera measures and a study on how the choice of training reflectances for the polynomial may alter the results.
	Address	Joensuu, Finland
	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	9781617388897	Medium
	Area		Expedition		Conference	CGIV/MCS
	Notes	CIC			Approved	no
	Call Number	CAT @ cat @ PBV2010a			Serial	1322
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	Author	Ariel Amato; Mikhail Mozerov; Andrew Bagdanov; Jordi Gonzalez
	Title	Accurate Moving Cast Shadow Suppression Based on Local Color Constancy detection			Type	Journal Article
	Year	2011	Publication	IEEE Transactions on Image Processing	Abbreviated Journal	TIP
	Volume	20	Issue	10	Pages	2954 - 2966
	Keywords
	Abstract	This paper describes a novel framework for detection and suppression of properly shadowed regions for most possible scenarios occurring in real video sequences. Our approach requires no prior knowledge about the scene, nor is it restricted to specific scene structures. Furthermore, the technique can detect both achromatic and chromatic shadows even in the presence of camouflage that occurs when foreground regions are very similar in color to shadowed regions. The method exploits local color constancy properties due to reflectance suppression over shadowed regions. To detect shadowed regions in a scene, the values of the background image are divided by values of the current frame in the RGB color space. We show how this luminance ratio can be used to identify segments with low gradient constancy, which in turn distinguish shadows from foreground. Experimental results on a collection of publicly available datasets illustrate the superior performance of our method compared with the most sophisticated, state-of-the-art shadow detection algorithms. These results show that our approach is robust and accurate over a broad range of shadow types and challenging video conditions.
	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	1057-7149	ISBN		Medium
	Area		Expedition		Conference
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ AMB2011			Serial	1716
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