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Author (down) Hugo Jair Escalante; Jose Martinez; Sergio Escalera; Victor Ponce; Xavier Baro
Title Improving Bag of Visual Words Representations with Genetic Programming Type Conference Article
Year 2015 Publication IEEE International Joint Conference on Neural Networks IJCNN2015 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract The bag of visual words is a well established representation in diverse computer vision problems. Taking inspiration from the fields of text mining and retrieval, this representation has proved to be very effective in a large number of domains.
In most cases, a standard term-frequency weighting scheme is considered for representing images and videos in computer vision. This is somewhat surprising, as there are many alternative ways of generating bag of words representations within the text processing community. This paper explores the use of alternative weighting schemes for landmark tasks in computer vision: image
categorization and gesture recognition. We study the suitability of using well-known supervised and unsupervised weighting schemes for such tasks. More importantly, we devise a genetic program that learns new ways of representing images and videos under the bag of visual words representation. The proposed method learns to combine term-weighting primitives trying to maximize the classification performance. Experimental results are reported in standard image and video data sets showing the effectiveness of the proposed evolutionary algorithm.
Address Killarney; Ireland; July 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 IJCNN
Notes HuPBA;MV Approved no
Call Number Admin @ si @ EME2015 Serial 2603
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Author (down) Huamin Ren; Weifeng Liu; Soren Ingvor Olsen; Sergio Escalera; Thomas B. Moeslund
Title Unsupervised Behavior-Specific Dictionary Learning for Abnormal Event Detection Type Conference Article
Year 2015 Publication 26th British Machine Vision Conference Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
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;MILAB Approved no
Call Number Admin @ si @ RLO2015 Serial 2658
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Author (down) Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados; R.Jain; D.Doermann
Title Novel Line Verification for Multiple Instance Focused Retrieval in Document Collections Type Conference Article
Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal
Volume Issue Pages 481-485
Keywords
Abstract
Address Nancy; France; August 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 ICDAR
Notes DAG; 600.077; 601.223; 600.084; 600.061 Approved no
Call Number Admin @ si @ GRK2015 Serial 2683
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Author (down) Hongxing Gao
Title Focused Structural Document Image Retrieval in Digital Mailroom Applications Type Book Whole
Year 2015 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
Keywords
Abstract In this work, we develop a generic framework that is able to handle the document retrieval problem in various scenarios such as searching for full page matches or retrieving the counterparts for specific document areas, focusing on their structural similarity or letting their visual resemblance to play a dominant role. Based on the spatial indexing technique, we propose to search for matches of local key-region pairs carrying both structural and visual information from the collection while a scheme allowing to adjust the relative contribution of structural and visual similarity is presented.
Based on the fact that the structure of documents is tightly linked with the distance among their elements, we firstly introduce an efficient detector named Distance Transform based Maximally Stable Extremal Regions (DTMSER). We illustrate that this detector is able to efficiently extract the structure of a document image as a dendrogram (hierarchical tree) of multi-scale key-regions that roughly correspond to letters, words and paragraphs. We demonstrate that, without benefiting from the structure information, the key-regions extracted by the DTMSER algorithm achieve better results comparing with state-of-the-art methods while much less amount of key-regions are employed.
We subsequently propose a pair-wise Bag of Words (BoW) framework to efficiently embed the explicit structure extracted by the DTMSER algorithm. We represent each document as a list of key-region pairs that correspond to the edges in the dendrogram where inclusion relationship is encoded. By employing those structural key-region pairs as the pooling elements for generating the histogram of features, the proposed method is able to encode the explicit inclusion relations into a BoW representation. The experimental results illustrate that the pair-wise BoW, powered by the embedded structural information, achieves remarkable improvement over the conventional BoW and spatial pyramidal BoW methods.
To handle various retrieval scenarios in one framework, we propose to directly query a series of key-region pairs, carrying both structure and visual information, from the collection. We introduce the spatial indexing techniques to the document retrieval community to speed up the structural relationship computation for key-region pairs. We firstly test the proposed framework in a full page retrieval scenario where structurally similar matches are expected. In this case, the pair-wise querying method achieves notable improvement over the BoW and spatial pyramidal BoW frameworks. Furthermore, we illustrate that the proposed method is also able to handle focused retrieval situations where the queries are defined as a specific interesting partial areas of the images. We examine our method on two types of focused queries: structure-focused and exact queries. The experimental results show that, the proposed generic framework obtains nearly perfect precision on both types of focused queries while it is the first framework able to tackle structure-focused queries, setting a new state of the art in the field.
Besides, we introduce a line verification method to check the spatial consistency among the matched key-region pairs. We propose a computationally efficient version of line verification through a two step implementation. We first compute tentative localizations of the query and subsequently employ them to divide the matched key-region pairs into several groups, then line verification is performed within each group while more precise bounding boxes are computed. We demonstrate that, comparing with the standard approach (based on RANSAC), the line verification proposed generally achieves much higher recall with slight loss on precision on specific queries.
Address January 2015
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor Josep Llados;Dimosthenis Karatzas;Marçal Rusiñol
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-84-943427-0-7 Medium
Area Expedition Conference
Notes DAG; 600.077 Approved no
Call Number Admin @ si @ Gao2015 Serial 2577
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Author (down) Hanne Kause; Patricia Marquez; Andrea Fuster; Aura Hernandez-Sabate; Luc Florack; Debora Gil; Hans van Assen
Title Quality Assessment of Optical Flow in Tagging MRI Type Conference Article
Year 2015 Publication 5th Dutch Bio-Medical Engineering Conference BME2015 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address The Netherlands; January 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 BME
Notes IAM; ADAS; 600.076; 600.075 Approved no
Call Number Admin @ si @ KMF2015 Serial 2616
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Author (down) Hanne Kause; Aura Hernandez-Sabate; Patricia Marquez; Andrea Fuster; Luc Florack; Hans van Assen; Debora Gil
Title Confidence Measures for Assessing the HARP Algorithm in Tagged Magnetic Resonance Imaging Type Book Chapter
Year 2015 Publication Statistical Atlases and Computational Models of the Heart. Revised selected papers of Imaging and Modelling Challenges 6th International Workshop, STACOM 2015, Held in Conjunction with MICCAI 2015 Abbreviated Journal
Volume 9534 Issue Pages 69-79
Keywords
Abstract Cardiac deformation and changes therein have been linked to pathologies. Both can be extracted in detail from tagged Magnetic Resonance Imaging (tMRI) using harmonic phase (HARP) images. Although point tracking algorithms have shown to have high accuracies on HARP images, these vary with position. Detecting and discarding areas with unreliable results is crucial for use in clinical support systems. This paper assesses the capability of two confidence measures (CMs), based on energy and image structure, for detecting locations with reduced accuracy in motion tracking results. These CMs were tested on a database of simulated tMRI images containing the most common artifacts that may affect tracking accuracy. CM performance is assessed based on its capability for HARP tracking error bounding and compared in terms of significant differences detected using a multi comparison analysis of variance that takes into account the most influential factors on HARP tracking performance. Results showed that the CM based on image structure was better suited to detect unreliable optical flow vectors. In addition, it was shown that CMs can be used to detect optical flow vectors with large errors in order to improve the optical flow obtained with the HARP tracking algorithm.
Address Munich; Germany; January 2015
Corporate Author Thesis
Publisher Springer International Publishing 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 978-3-319-28711-9 Medium
Area Expedition Conference STACOM
Notes ADAS; IAM; 600.075; 600.076; 600.060; 601.145 Approved no
Call Number Admin @ si @ KHM2015 Serial 2734
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Author (down) Gloria Fernandez Esparrach; Jorge Bernal; Cristina Rodriguez de Miguel; Debora Gil; Fernando Vilariño; Henry Cordova; Cristina Sanchez Montes; I.Araujo ; Maria Lopez Ceron; J.Llach; F. Javier Sanchez
Title Colonic polyps are correctly identified by a computer vision method using wm-dova energy maps Type Conference Article
Year 2015 Publication Proceedings of 23 United European- UEG Week 2015 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 UEG
Notes MV; IAM; 600.075;SIAI Approved no
Call Number Admin @ si @ FBR2015 Serial 2732
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Author (down) German Ros; Sebastian Ramos; Manuel Granados; Amir Bakhtiary; David Vazquez; Antonio Lopez
Title Vision-based Offline-Online Perception Paradigm for Autonomous Driving Type Conference Article
Year 2015 Publication IEEE Winter Conference on Applications of Computer Vision Abbreviated Journal
Volume Issue Pages 231 - 238
Keywords Autonomous Driving; Scene Understanding; SLAM; Semantic Segmentation
Abstract Autonomous driving is a key factor for future mobility. Properly perceiving the environment of the vehicles is essential for a safe driving, which requires computing accurate geometric and semantic information in real-time. In this paper, we challenge state-of-the-art computer vision algorithms for building a perception system for autonomous driving. An inherent drawback in the computation of visual semantics is the trade-off between accuracy and computational cost. We propose to circumvent this problem by following an offline-online strategy. During the offline stage dense 3D semantic maps are created. In the online stage the current driving area is recognized in the maps via a re-localization process, which allows to retrieve the pre-computed accurate semantics and 3D geometry in realtime. Then, detecting the dynamic obstacles we obtain a rich understanding of the current scene. We evaluate quantitatively our proposal in the KITTI dataset and discuss the related open challenges for the computer vision community.
Address Hawaii; January 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 ACDC Expedition Conference WACV
Notes ADAS; 600.076 Approved no
Call Number ADAS @ adas @ RRG2015 Serial 2499
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Author (down) Gerard Canal; Cecilio Angulo; Sergio Escalera
Title Gesture based Human Multi-Robot interaction Type Conference Article
Year 2015 Publication IEEE International Joint Conference on Neural Networks IJCNN2015 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract The emergence of robot applications for nontechnical users implies designing new ways of interaction between robotic platforms and users. The main goal of this work is the development of a gestural interface to interact with robots
in a similar way as humans do, allowing the user to provide information of the task with non-verbal communication. The gesture recognition application has been implemented using the Microsoft’s KinectTM v2 sensor. Hence, a real-time algorithm based on skeletal features is described to deal with both, static
gestures and dynamic ones, being the latter recognized using a weighted Dynamic Time Warping method. The gesture recognition application has been implemented in a multi-robot case.

A NAO humanoid robot is in charge of interacting with the users and respond to the visual signals they produce. Moreover, a wheeled Wifibot robot carries both the sensor and the NAO robot, easing navigation when necessary. A broad set of user tests have been carried out demonstrating that the system is, indeed, a
natural approach to human robot interaction, with a fast response and easy to use, showing high gesture recognition rates.
Address Killarney; Ireland; July 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 IJCNN
Notes HuPBA;MILAB Approved no
Call Number CAE2015a Serial 2651
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Author (down) G.Thorvaldsen; Joana Maria Pujadas-Mora; T.Andersen ; L.Eikvil; Josep Llados; Alicia Fornes; Anna Cabre
Title A Tale of two Transcriptions Type Journal
Year 2015 Publication Historical Life Course Studies Abbreviated Journal
Volume 2 Issue Pages 1-19
Keywords Nominative Sources; Census; Vital Records; Computer Vision; Optical Character Recognition; Word Spotting
Abstract non-indexed
This article explains how two projects implement semi-automated transcription routines: for census sheets in Norway and marriage protocols from Barcelona. The Spanish system was created to transcribe the marriage license books from 1451 to 1905 for the Barcelona area; one of the world’s longest series of preserved vital records. Thus, in the Project “Five Centuries of Marriages” (5CofM) at the Autonomous University of Barcelona’s Center for Demographic Studies, the Barcelona Historical Marriage Database has been built. More than 600,000 records were transcribed by 150 transcribers working online. The Norwegian material is cross-sectional as it is the 1891 census, recorded on one sheet per person. This format and the underlining of keywords for several variables made it more feasible to semi-automate data entry than when many persons are listed on the same page. While Optical Character Recognition (OCR) for printed text is scientifically mature, computer vision research is now focused on more difficult problems such as handwriting recognition. In the marriage project, document analysis methods have been proposed to automatically recognize the marriage licenses. Fully automatic recognition is still a challenge, but some promising results have been obtained. In Spain, Norway and elsewhere the source material is available as scanned pictures on the Internet, opening up the possibility for further international cooperation concerning automating the transcription of historic source materials. Like what is being done in projects to digitize printed materials, the optimal solution is likely to be a combination of manual transcription and machine-assisted recognition also for hand-written sources.
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 2352-6343 ISBN Medium
Area Expedition Conference
Notes DAG; 600.077; 602.006 Approved no
Call Number Admin @ si @ TPA2015 Serial 2582
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Author (down) G.Blasco; Simone Balocco; J.Puig; J.Sanchez-Gonzalez; W.Ricart; J.Daunis-I-Estadella; X.Molina; S.Pedraza; J.M.Fernandez-Real
Title Carotid pulse wave velocity by magnetic resonance imaging is increased in middle-aged subjects with the metabolic syndrome Type Journal Article
Year 2015 Publication International Journal of Cardiovascular Imaging Abbreviated Journal ICJI
Volume 31 Issue 3 Pages 603-612
Keywords Metabolic syndrome; Arterial stiffness; Pulse wave velocity; Carotid artery; Magnetic resonance
Abstract Arterial pulse wave velocity (PWV), an independent predictor of cardiovascular disease, physiologically increases with age; however, growing evidence suggests metabolic syndrome (MetS) accelerates this increase. Magnetic resonance imaging (MRI) enables reliable noninvasive assessment of arterial stiffness by measuring arterial PWV in specific vascular segments. We investigated the association between the presence of MetS and its components with carotid PWV (cPWV) in asymptomatic subjects without diabetes. We assessed cPWV by MRI in 61 individuals (mean age, 55.3 ± 14.1 years; median age, 55 years): 30 with MetS and 31 controls with similar age, sex, body mass index, and LDL-cholesterol levels. The study population was dichotomized by the median age. To remove the physiological association between PWV and age, unpaired t tests and multiple regression analyses were performed using the residuals of the regression between PWV and age. cPWV was higher in middle-aged subjects with MetS than in those without (p = 0.001), but no differences were found in elder subjects (p = 0.313). cPWV was associated with diastolic blood pressure (r = 0.276, p = 0.033) and waist circumference (r = 0.268, p = 0.038). The presence of MetS was associated with increased cPWV regardless of age, sex, blood pressure, and waist (p = 0.007). The MetS components contributing independently to an increased cPWV were hypertension (p = 0.018) and hypertriglyceridemia (p = 0.002). The presence of MetS is associated with an increased cPWV in middle-aged subjects. In particular, hypertension and hypertriglyceridemia may contribute to early progression of carotid stiffness.
Address
Corporate Author Thesis
Publisher Springer Netherlands Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1569-5794 ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number Admin @ si @ BBP2015 Serial 2670
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Author (down) G. Zahnd; Simone Balocco; A. Serusclat; P. Moulin; M. Orkisz; D. Vray
Title Progressive attenuation of the longitudinal kinetics in the common carotid artery: preliminary in vivo assessment Ultrasound in Medicine and Biology Type Journal Article
Year 2015 Publication Ultrasound in Medicine and Biology Abbreviated Journal UMB
Volume 41 Issue 1 Pages 339-345
Keywords Arterial stiffness; Atherosclerosis; Common carotid artery; Longitudinal kinetics; Motion tracking; Ultrasound imaging
Abstract Longitudinal kinetics (LOKI) of the arterial wall consists of the shearing motion of the intima-media complex over the adventitia layer in the direction parallel to the blood flow during the cardiac cycle. The aim of this study was to investigate the local variability of LOKI amplitude along the length of the vessel. By use of a previously validated motion-estimation framework, 35 in vivo longitudinal B-mode ultrasound cine loops of healthy common carotid arteries were analyzed. Results indicated that LOKI amplitude is progressively attenuated along the length of the artery, as it is larger in regions located on the proximal side of the image (i.e., toward the heart) and smaller in regions located on the distal side of the image (i.e., toward the head), with an average attenuation coefficient of -2.5 ± 2.0%/mm. Reported for the first time in this study, this phenomenon is likely to be of great importance in improving understanding of atherosclerosis mechanisms, and has the potential to be a novel index of arterial stiffness.
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 MILAB Approved no
Call Number Admin @ si @ ZBS2014 Serial 2556
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Author (down) G. Lisanti; I. Masi; Andrew Bagdanov; Alberto del Bimbo
Title Person Re-identification by Iterative Re-weighted Sparse Ranking Type Journal Article
Year 2015 Publication IEEE Transactions on Pattern Analysis and Machine Intelligence Abbreviated Journal TPAMI
Volume 37 Issue 8 Pages 1629 - 1642
Keywords
Abstract In this paper we introduce a method for person re-identification based on discriminative, sparse basis expansions of targets in terms of a labeled gallery of known individuals. We propose an iterative extension to sparse discriminative classifiers capable of ranking many candidate targets. The approach makes use of soft- and hard- re-weighting to redistribute energy among the most relevant contributing elements and to ensure that the best candidates are ranked at each iteration. Our approach also leverages a novel visual descriptor which we show to be discriminative while remaining robust to pose and illumination variations. An extensive comparative evaluation is given demonstrating that our approach achieves state-of-the-art performance on single- and multi-shot person re-identification scenarios on the VIPeR, i-LIDS, ETHZ, and CAVIAR4REID datasets. The combination of our descriptor and iterative sparse basis expansion improves state-of-the-art rank-1 performance by six percentage points on VIPeR and by 20 on CAVIAR4REID compared to other methods with a single gallery image per person. With multiple gallery and probe images per person our approach improves by 17 percentage points the state-of-the-art on i-LIDS and by 72 on CAVIAR4REID at rank-1. The approach is also quite efficient, capable of single-shot person re-identification over galleries containing hundreds of individuals at about 30 re-identifications per second.
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 LAMP; 601.240; 600.079 Approved no
Call Number Admin @ si @ LMB2015 Serial 2557
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Author (down) Frederic Sampedro; Sergio Escalera; Anna Domenech; Ignasi Carrio
Title Automatic Tumor Volume Segmentation in Whole-Body PET/CT Scans: A Supervised Learning Approach Source Type Journal Article
Year 2015 Publication Journal of Medical Imaging and Health Informatics Abbreviated Journal JMIHI
Volume 5 Issue 2 Pages 192-201
Keywords CONTEXTUAL CLASSIFICATION; PET/CT; SUPERVISED LEARNING; TUMOR SEGMENTATION; WHOLE BODY
Abstract Whole-body 3D PET/CT tumoral volume segmentation provides relevant diagnostic and prognostic information in clinical oncology and nuclear medicine. Carrying out this procedure manually by a medical expert is time consuming and suffers from inter- and intra-observer variabilities. In this paper, a completely automatic approach to this task is presented. First, the problem is stated and described both in clinical and technological terms. Then, a novel supervised learning segmentation framework is introduced. The segmentation by learning approach is defined within a Cascade of Adaboost classifiers and a 3D contextual proposal of Multiscale Stacked Sequential Learning. Segmentation accuracy results on 200 Breast Cancer whole body PET/CT volumes show mean 49% sensitivity, 99.993% specificity and 39% Jaccard overlap Index, which represent good performance results both at the clinical and technological level.
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 @ SED2015 Serial 2584
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Author (down) Frederic Sampedro; Sergio Escalera
Title Spatial codification of label predictions in Multi-scale Stacked Sequential Learning: A case study on multi-class medical volume segmentation Type Journal Article
Year 2015 Publication IET Computer Vision Abbreviated Journal IETCV
Volume 9 Issue 3 Pages 439 - 446
Keywords
Abstract In this study, the authors propose the spatial codification of label predictions within the multi-scale stacked sequential learning (MSSL) framework, a successful learning scheme to deal with non-independent identically distributed data entries. After providing a motivation for this objective, they describe its theoretical framework based on the introduction of the blurred shape model as a smart descriptor to codify the spatial distribution of the predicted labels and define the new extended feature set for the second stacked classifier. They then particularise this scheme to be applied in volume segmentation applications. Finally, they test the implementation of the proposed framework in two medical volume segmentation datasets, obtaining significant performance improvements (with a 95% of confidence) in comparison to standard Adaboost classifier and classical MSSL approaches.
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 1751-9632 ISBN Medium
Area Expedition Conference
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ SaE2015 Serial 2551
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