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Author | Agata Lapedriza; David Masip; Jordi Vitria | ||||
Title | Subject Recognition Using a New Approach for Feature Extraction | Type | Conference Article | ||
Year | 2008 | Publication | 3rd International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
Volume | 2 | Issue | Pages ![]() |
61–66 | |
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Address | Madeira (Portugal) | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | VISAPP | ||
Notes | OR; MV | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ LMV2008a | Serial | 980 | ||
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Author | Marta Nuñez-Garcia; Sonja Simpraga; M.Angeles Jurado; Maite Garolera; Roser Pueyo; Laura Igual | ||||
Title | FADR: Functional-Anatomical Discriminative Regions for rest fMRI Characterization | Type | Conference Article | ||
Year | 2015 | Publication | Machine Learning in Medical Imaging, Proceedings of 6th International Workshop, MLMI 2015, Held in Conjunction with MICCAI 2015 | Abbreviated Journal | |
Volume | Issue | Pages ![]() |
61-68 | ||
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Address | Munich; Germany; October 2015 | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | MLMI | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ NSJ2015 | Serial | 2674 | ||
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Author | Dimosthenis Karatzas; Lluis Gomez; Marçal Rusiñol; Anguelos Nicolaou | ||||
Title | The Robust Reading Competition Annotation and Evaluation Platform | Type | Conference Article | ||
Year | 2018 | Publication | 13th IAPR International Workshop on Document Analysis Systems | Abbreviated Journal | |
Volume | Issue | Pages ![]() |
61-66 | ||
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Abstract | The ICDAR Robust Reading Competition (RRC), initiated in 2003 and reestablished in 2011, has become the defacto evaluation standard for the international community. Concurrent with its second incarnation in 2011, a continuous
effort started to develop an online framework to facilitate the hosting and management of competitions. This short paper briefly outlines the Robust Reading Competition Annotation and Evaluation Platform, the backbone of the Robust Reading Competition, comprising a collection of tools and processes that aim to simplify the management and annotation of data, and to provide online and offline performance evaluation and analysis services. |
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Address | Viena; Austria; April 2018 | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | DAS | ||
Notes | DAG; 600.084; 600.121 | Approved | no | ||
Call Number | KGR2018 | Serial | 3103 | ||
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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 | |||
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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 | Carles Sanchez; Debora Gil; Jorge Bernal; F. Javier Sanchez; Marta Diez-Ferrer; Antoni Rosell | ||||
Title | Navigation Path Retrieval from Videobronchoscopy using Bronchial Branches | Type | Conference Article | ||
Year | 2016 | Publication | 19th International Conference on Medical Image Computing and Computer Assisted Intervention Workshops | Abbreviated Journal | |
Volume | 9401 | Issue | Pages ![]() |
62-70 | |
Keywords | Bronchoscopy navigation; Lumen center; Brochial branches; Navigation path; Videobronchoscopy | ||||
Abstract | Bronchoscopy biopsy can be used to diagnose lung cancer without risking complications of other interventions like transthoracic needle aspiration. During bronchoscopy, the clinician has to navigate through the bronchial tree to the target lesion. A main drawback is the difficulty to check whether the exploration is following the correct path. The usual guidance using fluoroscopy implies repeated radiation of the clinician, while alternative systems (like electromagnetic navigation) require specific equipment that increases intervention costs. We propose to compute the navigated path using anatomical landmarks extracted from the sole analysis of videobronchoscopy images. Such landmarks allow matching the current exploration to the path previously planned on a CT to indicate clinician whether the planning is being correctly followed or not. We present a feasibility study of our landmark based CT-video matching using bronchoscopic videos simulated on a virtual bronchoscopy interactive interface. | ||||
Address | Quebec; Canada; September 2016 | ||||
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Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | MICCAIW | ||
Notes | IAM; MV; 600.060; 600.075 | Approved | no | ||
Call Number | Admin @ si @ SGB2016 | Serial | 2885 | ||
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Author | Carola Figueroa Flores; Abel Gonzalez-Garcia; Joost Van de Weijer; Bogdan Raducanu | ||||
Title | Saliency for fine-grained object recognition in domains with scarce training data | Type | Journal Article | ||
Year | 2019 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 94 | Issue | Pages ![]() |
62-73 | |
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Abstract | This paper investigates the role of saliency to improve the classification accuracy of a Convolutional Neural Network (CNN) for the case when scarce training data is available. Our approach consists in adding a saliency branch to an existing CNN architecture which is used to modulate the standard bottom-up visual features from the original image input, acting as an attentional mechanism that guides the feature extraction process. The main aim of the proposed approach is to enable the effective training of a fine-grained recognition model with limited training samples and to improve the performance on the task, thereby alleviating the need to annotate a large dataset. The vast majority of saliency methods are evaluated on their ability to generate saliency maps, and not on their functionality in a complete vision pipeline. Our proposed pipeline allows to evaluate saliency methods for the high-level task of object recognition. We perform extensive experiments on various fine-grained datasets (Flowers, Birds, Cars, and Dogs) under different conditions and show that saliency can considerably improve the network’s performance, especially for the case of scarce training data. Furthermore, our experiments show that saliency methods that obtain improved saliency maps (as measured by traditional saliency benchmarks) also translate to saliency methods that yield improved performance gains when applied in an object recognition pipeline. | ||||
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Notes | LAMP; OR; 600.109; 600.141; 600.120 | Approved | no | ||
Call Number | Admin @ si @ FGW2019 | Serial | 3264 | ||
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Author | Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados | ||||
Title | Categorization of Digital Ink Elements using Spectral Features | Type | Conference Article | ||
Year | 2007 | Publication | Seventh IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
Volume | Issue | Pages ![]() |
63–64 | ||
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Address | Curitiba (Brazil) | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | GREC | ||
Notes | DAG | Approved | no | ||
Call Number | DAG @ dag @ RSL2007c | Serial | 888 | ||
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Author | Agata Lapedriza; Jaume Garcia; Ernest Valveny; Robert Benavente; Miquel Ferrer; Gemma Sanchez | ||||
Title | Una experiencia de aprenentatge basada en projectes en el ambit de la informatica | Type | Miscellaneous | ||
Year | 2008 | Publication | V Jornades d’Innovacio Docent (UAB) | Abbreviated Journal | |
Volume | Issue | Pages ![]() |
63 | ||
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Address | Bellaterra (Spain) | ||||
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Area | Expedition | Conference | |||
Notes | OR; IAM; DAG; CIC; MV | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ LGV2008 | Serial | 1030 | ||
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Author | Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados | ||||
Title | Browsing Heterogeneous Document Collections by a Segmentation-Free Word Spotting Method | Type | Conference Article | ||
Year | 2011 | Publication | 11th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages ![]() |
63-67 | ||
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Abstract | In this paper, we present a segmentation-free word spotting method that is able to deal with heterogeneous document image collections. We propose a patch-based framework where patches are represented by a bag-of-visual-words model powered by SIFT descriptors. A later refinement of the feature vectors is performed by applying the latent semantic indexing technique. The proposed method performs well on both handwritten and typewritten historical document images. We have also tested our method on documents written in non-Latin scripts. | ||||
Address | Beijing, China | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICDAR | ||
Notes | DAG;ADAS | Approved | no | ||
Call Number | Admin @ si @ RAT2011 | Serial | 1788 | ||
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Author | Olivier Penacchio; Laura Dempere-Marco; Xavier Otazu | ||||
Title | A Neurodynamical Model Of Brightness Induction In V1 Following Static And Dynamic Contextual Influences | Type | Abstract | ||
Year | 2012 | Publication | 8th Federation of European Neurosciences | Abbreviated Journal | |
Volume | 6 | Issue | Pages ![]() |
63-64 | |
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Abstract | Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Although striate cortex is traditionally regarded as an area mostly responsive to ensory (i.e. retinal) information,
neurophysiological evidence suggests that perceived brightness information mightbe explicitly represented in V1. Such evidence has been observed both in anesthetised cats where neuronal response modulations have been found to follow luminance changes outside the receptive felds and in human fMRI measurements. In this work, possible neural mechanisms that ofer a plausible explanation for such phenomenon are investigated. To this end, we consider the model proposed by Z.Li (Li, Network:Comput. Neural Syst., 10 (1999)) which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual infuences, i.e. layer 2-3 pyramidal cells, interneurons, and horizontal intracortical connections. This model has reproduced other phenomena such as contour detection and preattentive segmentation, which share with brightness induction the relevant efect of contextual infuences. We have extended the original model such that the input to the network is obtained from a complete multiscale and multiorientation wavelet decomposition, thereby allowing the recovery of an image refecting the perceived intensity. The proposed model successfully accounts for well known psychophysical efects for static contexts (among them: the White's and modifed White's efects, the Todorovic, Chevreul, achromatic ring patterns, and grating induction efects) and also for brigthness induction in dynamic contexts defned by modulating the luminance of surrounding areas (e.g. the brightness of a static central area is perceived to vary in antiphase to the sinusoidal luminance changes of its surroundings). This work thus suggests that intra-cortical interactions in V1 could partially explain perceptual brightness induction efects and reveals how a common general architecture may account for several different fundamental processes emerging early in the visual processing pathway. |
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | FENS | ||
Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ PDO2012b | Serial | 2181 | ||
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Author | Debora Gil; Rosa Maria Ortiz; Carles Sanchez; Antoni Rosell | ||||
Title | Objective endoscopic measurements of central airway stenosis. A pilot study | Type | Journal Article | ||
Year | 2018 | Publication | Respiration | Abbreviated Journal | RES |
Volume | 95 | Issue | Pages ![]() |
63–69 | |
Keywords | Bronchoscopy; Tracheal stenosis; Airway stenosis; Computer-assisted analysis | ||||
Abstract | Endoscopic estimation of the degree of stenosis in central airway obstruction is subjective and highly variable. Objective: To determine the benefits of using SENSA (System for Endoscopic Stenosis Assessment), an image-based computational software, for obtaining objective stenosis index (SI) measurements among a group of expert bronchoscopists and general pulmonologists. Methods: A total of 7 expert bronchoscopists and 7 general pulmonologists were enrolled to validate SENSA usage. The SI obtained by the physicians and by SENSA were compared with a reference SI to set their precision in SI computation. We used SENSA to efficiently obtain this reference SI in 11 selected cases of benign stenosis. A Web platform with three user-friendly microtasks was designed to gather the data. The users had to visually estimate the SI from videos with and without contours of the normal and the obstructed area provided by SENSA. The users were able to modify the SENSA contours to define the reference SI using morphometric bronchoscopy. Results: Visual SI estimation accuracy was associated with neither bronchoscopic experience (p = 0.71) nor the contours of the normal and the obstructed area provided by the system (p = 0.13). The precision of the SI by SENSA was 97.7% (95% CI: 92.4-103.7), which is significantly better than the precision of the SI by visual estimation (p < 0.001), with an improvement by at least 15%. Conclusion: SENSA provides objective SI measurements with a precision of up to 99.5%, which can be calculated from any bronchoscope using an affordable scalable interface. Providing normal and obstructed contours on bronchoscopic videos does not improve physicians' visual estimation of the SI. | ||||
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Notes | IAM; 600.075; 600.096; 600.145 | Approved | no | ||
Call Number | Admin @ si @ GOS2018 | Serial | 3043 | ||
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Author | Debora Gil; Ruth Aris; Agnes Borras; Esmitt Ramirez; Rafael Sebastian; Mariano Vazquez | ||||
Title | Influence of fiber connectivity in simulations of cardiac biomechanics | Type | Journal Article | ||
Year | 2019 | Publication | International Journal of Computer Assisted Radiology and Surgery | Abbreviated Journal | IJCAR |
Volume | 14 | Issue | 1 | Pages ![]() |
63–72 |
Keywords | Cardiac electromechanical simulations; Diffusion tensor imaging; Fiber connectivity | ||||
Abstract | PURPOSE:
Personalized computational simulations of the heart could open up new improved approaches to diagnosis and surgery assistance systems. While it is fully recognized that myocardial fiber orientation is central for the construction of realistic computational models of cardiac electromechanics, the role of its overall architecture and connectivity remains unclear. Morphological studies show that the distribution of cardiac muscular fibers at the basal ring connects epicardium and endocardium. However, computational models simplify their distribution and disregard the basal loop. This work explores the influence in computational simulations of fiber distribution at different short-axis cuts. METHODS: We have used a highly parallelized computational solver to test different fiber models of ventricular muscular connectivity. We have considered two rule-based mathematical models and an own-designed method preserving basal connectivity as observed in experimental data. Simulated cardiac functional scores (rotation, torsion and longitudinal shortening) were compared to experimental healthy ranges using generalized models (rotation) and Mahalanobis distances (shortening, torsion). RESULTS: The probability of rotation was significantly lower for ruled-based models [95% CI (0.13, 0.20)] in comparison with experimental data [95% CI (0.23, 0.31)]. The Mahalanobis distance for experimental data was in the edge of the region enclosing 99% of the healthy population. CONCLUSIONS: Cardiac electromechanical simulations of the heart with fibers extracted from experimental data produce functional scores closer to healthy ranges than rule-based models disregarding architecture connectivity. |
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Notes | IAM; 600.096; 601.323; 600.139; 600.145 | Approved | no | ||
Call Number | Admin @ si @ GAB2019a | Serial | 3133 | ||
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Author | Meysam Madadi; Sergio Escalera; Alex Carruesco Llorens; Carlos Andujar; Xavier Baro; Jordi Gonzalez | ||||
Title | Top-down model fitting for hand pose recovery in sequences of depth images | Type | Journal Article | ||
Year | 2018 | Publication | Image and Vision Computing | Abbreviated Journal | IMAVIS |
Volume | 79 | Issue | Pages ![]() |
63-75 | |
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Abstract | State-of-the-art approaches on hand pose estimation from depth images have reported promising results under quite controlled considerations. In this paper we propose a two-step pipeline for recovering the hand pose from a sequence of depth images. The pipeline has been designed to deal with images taken from any viewpoint and exhibiting a high degree of finger occlusion. In a first step we initialize the hand pose using a part-based model, fitting a set of hand components in the depth images. In a second step we consider temporal data and estimate the parameters of a trained bilinear model consisting of shape and trajectory bases. We evaluate our approach on a new created synthetic hand dataset along with NYU and MSRA real datasets. Results demonstrate that the proposed method outperforms the most recent pose recovering approaches, including those based on CNNs. | ||||
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Notes | HUPBA; 600.098 | Approved | no | ||
Call Number | Admin @ si @ MEC2018 | Serial | 3203 | ||
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Author | Sangheeta Roy; Palaiahnakote Shivakumara; Namita Jain; Vijeta Khare; Anjan Dutta; Umapada Pal; Tong Lu | ||||
Title | Rough-Fuzzy based Scene Categorization for Text Detection and Recognition in Video | Type | Journal Article | ||
Year | 2018 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 80 | Issue | Pages ![]() |
64-82 | |
Keywords | Rough set; Fuzzy set; Video categorization; Scene image classification; Video text detection; Video text recognition | ||||
Abstract | Scene image or video understanding is a challenging task especially when number of video types increases drastically with high variations in background and foreground. This paper proposes a new method for categorizing scene videos into different classes, namely, Animation, Outlet, Sports, e-Learning, Medical, Weather, Defense, Economics, Animal Planet and Technology, for the performance improvement of text detection and recognition, which is an effective approach for scene image or video understanding. For this purpose, at first, we present a new combination of rough and fuzzy concept to study irregular shapes of edge components in input scene videos, which helps to classify edge components into several groups. Next, the proposed method explores gradient direction information of each pixel in each edge component group to extract stroke based features by dividing each group into several intra and inter planes. We further extract correlation and covariance features to encode semantic features located inside planes or between planes. Features of intra and inter planes of groups are then concatenated to get a feature matrix. Finally, the feature matrix is verified with temporal frames and fed to a neural network for categorization. Experimental results show that the proposed method outperforms the existing state-of-the-art methods, at the same time, the performances of text detection and recognition methods are also improved significantly due to categorization. | ||||
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Notes | DAG; 600.097; 600.121 | Approved | no | ||
Call Number | Admin @ si @ RSJ2018 | Serial | 3096 | ||
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Author | Vacit Oguz Yazici; Joost Van de Weijer; Arnau Ramisa | ||||
Title | Color Naming for Multi-Color Fashion Items | Type | Conference Article | ||
Year | 2018 | Publication | 6th World Conference on Information Systems and Technologies | Abbreviated Journal | |
Volume | 747 | Issue | Pages ![]() |
64-73 | |
Keywords | Deep learning; Color; Multi-label | ||||
Abstract | There exists a significant amount of research on color naming of single colored objects. However in reality many fashion objects consist of multiple colors. Currently, searching in fashion datasets for multi-colored objects can be a laborious task. Therefore, in this paper we focus on color naming for images with multi-color fashion items. We collect a dataset, which consists of images which may have from one up to four colors. We annotate the images with the 11 basic colors of the English language. We experiment with several designs for deep neural networks with different losses. We show that explicitly estimating the number of colors in the fashion item leads to improved results. | ||||
Address | Naples; March 2018 | ||||
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Area | Expedition | Conference | WORLDCIST | ||
Notes | LAMP; 600.109; 601.309; 600.120 | Approved | no | ||
Call Number | Admin @ si @ YWR2018 | Serial | 3161 | ||
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