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Author Ali Furkan Biten; R. Tito; Andres Mafla; Lluis Gomez; Marçal Rusiñol; M. Mathew; C.V. Jawahar; Ernest Valveny; Dimosthenis Karatzas
Title ICDAR 2019 Competition on Scene Text Visual Question Answering Type Conference Article
Year 2019 Publication (down) 3rd Workshop on Closing the Loop Between Vision and Language, in conjunction with ICCV2019 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract This paper presents final results of ICDAR 2019 Scene Text Visual Question Answering competition (ST-VQA). ST-VQA introduces an important aspect that is not addressed
by any Visual Question Answering system up to date, namely the incorporation of scene text to answer questions asked about an image. The competition introduces a new dataset comprising 23, 038 images annotated with 31, 791 question / answer pairs where the answer is always grounded on text instances present in the image. The images are taken from 7 different public computer vision datasets, covering a wide range of scenarios.
The competition was structured in three tasks of increasing difficulty, that require reading the text in a scene and understanding it in the context of the scene, to correctly answer a given question. A novel evaluation metric is presented, which elegantly assesses both key capabilities expected from an optimal model: text recognition and image understanding. A detailed analysis of results from different participants is showcased, which provides insight into the current capabilities of VQA systems that can read. We firmly believe the dataset proposed in this challenge will be an important milestone to consider towards a path of more robust and general models that
can exploit scene text to achieve holistic image understanding.
Address Sydney; Australia; 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 CLVL
Notes DAG; 600.129; 601.338; 600.135; 600.121 Approved no
Call Number Admin @ si @ BTM2019a Serial 3284
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Author Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate
Title Is there a pattern of Chromosome territoriality along mice spermatogenesis? Type Conference Article
Year 2017 Publication (down) 3rd Spanish MeioNet Meeting Abstract Book Abbreviated Journal
Volume Issue Pages 55-56
Keywords
Abstract
Address Miraflores de la Sierra; Madrid; June 2017
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 MEIONET
Notes IAM; 600.096; 600.145 Approved no
Call Number Admin @ si @ Serial 2958
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Author Jorge Bernal; Joan M. Nuñez; F. Javier Sanchez; Fernando Vilariño
Title Polyp Segmentation Method in Colonoscopy Videos by means of MSA-DOVA Energy Maps Calculation Type Conference Article
Year 2014 Publication (down) 3rd MICCAI Workshop on Clinical Image-based Procedures: Translational Research in Medical Imaging Abbreviated Journal
Volume 8680 Issue Pages 41-49
Keywords Image segmentation; Polyps; Colonoscopy; Valley information; Energy maps
Abstract In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation.
Address Boston; USA; September 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 CLIP
Notes MV; 600.060; 600.044; 600.047;SIAI Approved no
Call Number Admin @ si @ BNS2014 Serial 2502
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Author Konstantia Georgouli; Katerine Diaz; Jesus Martinez del Rincon; Anastasios Koidis
Title Building generic, easily-updatable chemometric models with harmonisation and augmentation features: The case of FTIR vegetable oils classification Type Conference Article
Year 2017 Publication (down) 3rd Ιnternational Conference Metrology Promoting Standardization and Harmonization in Food and Nutrition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Thessaloniki; Greece; October 2017
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 IMEKOFOODS
Notes ADAS; 600.118 Approved no
Call Number Admin @ si @ GDM2017 Serial 3081
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Author Anna Salvatella; Maria Vanrell; Juan J. Villanueva
Title Texture Description based on Subtexture Components, 3rd International Workshop on Texture Syntesis and Analysis Type Conference Article
Year 2003 Publication (down) 3rd International Workshop on Texture Synthesis and Analysis, Abbreviated Journal
Volume Issue Pages 77–82
Keywords
Abstract
Address Nice
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 1-904410-11-1 Medium
Area Expedition Conference
Notes CIC Approved no
Call Number CAT @ cat @ SVV2003 Serial 422
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Author Arnau Baro; Carles Badal; Pau Torras; Alicia Fornes
Title Handwritten Historical Music Recognition through Sequence-to-Sequence with Attention Mechanism Type Conference Article
Year 2022 Publication (down) 3rd International Workshop on Reading Music Systems (WoRMS2021) Abbreviated Journal
Volume Issue Pages 55-59
Keywords Optical Music Recognition; Digits; Image Classification
Abstract Despite decades of research in Optical Music Recognition (OMR), the recognition of old handwritten music scores remains a challenge because of the variabilities in the handwriting styles, paper degradation, lack of standard notation, etc. Therefore, the research in OMR systems adapted to the particularities of old manuscripts is crucial to accelerate the conversion of music scores existing in archives into digital libraries, fostering the dissemination and preservation of our music heritage. In this paper we explore the adaptation of sequence-to-sequence models with attention mechanism (used in translation and handwritten text recognition) and the generation of specific synthetic data for recognizing old music scores. The experimental validation demonstrates that our approach is promising, especially when compared with long short-term memory neural networks.
Address July 23, 2021, Alicante (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 WoRMS
Notes DAG; 600.121; 600.162; 602.230; 600.140 Approved no
Call Number Admin @ si @ BBT2022 Serial 3734
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Author Debora Gil; Aura Hernandez-Sabate; Antoni Carol; Oriol Rodriguez; Petia Radeva
Title A Deterministic-Statistic Adventitia Detection in IVUS Images Type Conference Article
Year 2005 Publication (down) 3rd International workshop on International Workshop on Functional Imaging and Modeling of the Heart Abbreviated Journal
Volume Issue Pages 65-74
Keywords Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation
Abstract Plaque analysis in IVUS planes needs accurate intima and adventitia models. Large variety in adventitia descriptors difficulties its detection and motivates using a classification strategy for selecting points on the structure. Whatever the set of descriptors used, the selection stage suffers from fake responses due to noise and uncompleted true curves. In order to smooth background noise while strengthening responses, we apply a restricted anisotropic filter that homogenizes grey levels along the image significant structures. Candidate points are extracted by means of a simple semi supervised adaptive classification of the filtered image response to edge and calcium detectors. The final model is obtained by interpolating the former line segments with an anisotropic contour closing technique based on functional extension principles.
Address Barcelona; June 2005
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 FIMH
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ RMF2005 Serial 1524
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Author Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich
Title Perception Based Representations for Computational Colour Type Conference Article
Year 2011 Publication (down) 3rd International Workshop on Computational Color Imaging Abbreviated Journal
Volume 6626 Issue Pages 16-30
Keywords colour perception, induction, naming, psychophysical data, saliency, segmentation
Abstract The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space.
Address Milan, Italy
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Editor Raimondo Schettini, Shoji Tominaga, Alain Trémeau
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-20403-6 Medium
Area Expedition Conference CCIW
Notes CIC Approved no
Call Number Admin @ si @ VMB2011 Serial 1733
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Author Isabel Guitart; Jordi Conesa; Luis Villarejo; Agata Lapedriza; David Masip; Antoni Perez; Elena Planas
Title Opinion Mining on Educational Resources at the Open University of Catalonia Type Conference Article
Year 2013 Publication (down) 3rd International Workshop on Adaptive Learning via Interactive, Collaborative and Emotional approaches. In conjunction with CISIS 2013: The 7th International Conference on Complex, Intelligent, and Software Intensive Systems Abbreviated Journal
Volume Issue Pages 385 - 390
Keywords
Abstract In order to make improvements to teaching, it is vital to know what students think of the way they are taught. With that purpose in mind, exhaustively analyzing the forums associated with the subjects taught at the Universitat Oberta de Cataluya (UOC) would be extremely helpful, as the university's students often post comments on their learning experiences in them. Exploiting the content of such forums is not a simple undertaking. The volume of data involved is very large, and performing the task manually would require a great deal of effort from lecturers. As a first step to solve this problem, we propose a tool to automatically analyze the posts in forums of communities of UOC students and teachers, with a view to systematically mining the opinions they contain. This article defines the architecture of such tool and explains how lexical-semantic and language technology resources can be used to that end. For pilot testing purposes, the tool has been used to identify students' opinions on the UOC's Business Intelligence master's degree course during the last two years. The paper discusses the results of such test. The contribution of this paper is twofold. Firstly, it demonstrates the feasibility of using natural language parsing techniques to help teachers to make decisions. Secondly, it introduces a simple tool that can be refined and adapted to a virtual environment for the purpose in question.
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 978-0-7695-4992-7 Medium
Area Expedition Conference ALICE
Notes OR;MV Approved no
Call Number GCV2013 Serial 2268
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Author Jose A. Garcia; David Masip; Valerio Sbragaglia; Jacopo Aguzzi
Title Using ORB, BoW and SVM to identificate and track tagged Norway lobster Nephrops Norvegicus (L.) Type Conference Article
Year 2016 Publication (down) 3rd International Conference on Maritime Technology and Engineering Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Sustainable capture policies of many species strongly depend on the understanding of their social behaviour. Nevertheless, the analysis of emergent behaviour in marine species poses several challenges. Usually animals are captured and observed in tanks, and their behaviour is inferred from their dynamics and interactions. Therefore, researchers must deal with thousands of hours of video data. Without loss of generality, this paper proposes a computer
vision approach to identify and track specific species, the Norway lobster, Nephrops norvegicus. We propose an identification scheme were animals are marked using black and white tags with a geometric shape in the center (holed
triangle, filled triangle, holed circle and filled circle). Using a massive labelled dataset; we extract local features based on the ORB descriptor. These features are a posteriori clustered, and we construct a Bag of Visual Words feature vector per animal. This approximation yields us invariance to rotation
and translation. A SVM classifier achieves generalization results above 99%. In a second contribution, we will make the code and training data publically available.
Address Lisboa; Portugal; July 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 MARTECH
Notes OR;MV; Approved no
Call Number Admin @ si @ GMS2016b Serial 2817
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Author Adriana Romero; Nicolas Ballas; Samira Ebrahimi Kahou; Antoine Chassang; Carlo Gatta; Yoshua Bengio
Title FitNets: Hints for Thin Deep Nets Type Conference Article
Year 2015 Publication (down) 3rd International Conference on Learning Representations ICLR2015 Abbreviated Journal
Volume Issue Pages
Keywords Computer Science ; Learning; Computer Science ;Neural and Evolutionary Computing
Abstract While depth tends to improve network performances, it also makes gradient-based training more difficult since deeper networks tend to be more non-linear. The recently proposed knowledge distillation approach is aimed at obtaining small and fast-to-execute models, and it has shown that a student network could imitate the soft output of a larger teacher network or ensemble of networks. In this paper, we extend this idea to allow the training of a student that is deeper and thinner than the teacher, using not only the outputs but also the intermediate representations learned by the teacher as hints to improve the training process and final performance of the student. Because the student intermediate hidden layer will generally be smaller than the teacher's intermediate hidden layer, additional parameters are introduced to map the student hidden layer to the prediction of the teacher hidden layer. This allows one to train deeper students that can generalize better or run faster, a trade-off that is controlled by the chosen student capacity. For example, on CIFAR-10, a deep student network with almost 10.4 times less parameters outperforms a larger, state-of-the-art teacher network.
Address San Diego; CA; May 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 ICLR
Notes MILAB Approved no
Call Number Admin @ si @ RBK2015 Serial 2593
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Author George A. Triantafyllid; Nikolaos Thomos; Cristina Cañero; P. Vieyres; Michael G. Strintzis
Title A User Interface for Mobile Robotized Tele-Echography Type Miscellaneous
Year 2005 Publication (down) 3rd International Conference on Imaging Technologies in Biomedical Sciences (ITBS 2005) Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Milos Island (Greece)
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 Admin @ si @ TTC2005 Serial 587
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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 (down) 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 Arnau Baro; Jialuo Chen; Alicia Fornes; Beata Megyesi
Title Towards a generic unsupervised method for transcription of encoded manuscripts Type Conference Article
Year 2019 Publication (down) 3rd International Conference on Digital Access to Textual Cultural Heritage Abbreviated Journal
Volume Issue Pages 73-78
Keywords A. Baró, J. Chen, A. Fornés, B. Megyesi.
Abstract Historical ciphers, a special type of manuscripts, contain encrypted information, important for the interpretation of our history. The first step towards decipherment is to transcribe the images, either manually or by automatic image processing techniques. Despite the improvements in handwritten text recognition (HTR) thanks to deep learning methodologies, the need of labelled data to train is an important limitation. Given that ciphers often use symbol sets across various alphabets and unique symbols without any transcription scheme available, these supervised HTR techniques are not suitable to transcribe ciphers. In this paper we propose an un-supervised method for transcribing encrypted manuscripts based on clustering and label propagation, which has been successfully applied to community detection in networks. We analyze the performance on ciphers with various symbol sets, and discuss the advantages and drawbacks compared to supervised HTR methods.
Address Brussels; May 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 DATeCH
Notes DAG; 600.097; 600.140; 600.121 Approved no
Call Number Admin @ si @ BCF2019 Serial 3276
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Author Sergio Escalera; Oriol Pujol; Petia Radeva
Title Loss-Weighted Decoding for Error-Correcting Output Coding Type Conference Article
Year 2008 Publication (down) 3rd International Conference on Computer Vision Theory and Applications, Abbreviated Journal
Volume 2 Issue Pages 117–122
Keywords
Abstract
Address Madeira (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 VISAPP
Notes MILAB;HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ EPR2008a Serial 964
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