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| Author | Marçal Rusiñol; Josep Llados | ||||
| Title | Symbol Spotting in Digital Libraries:Focused Retrieval over Graphic-rich Document Collections | Type | Book Whole | ||
| Year | 2010 | Publication | Symbol Spotting in Digital Libraries:Focused Retrieval over Graphic-rich Document Collections | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Focused Retrieval , Graphical Pattern Indexation,Graphics Recognition ,Pattern Recognition , Performance Evaluation , Symbol Description ,Symbol Spotting | ||||
| Abstract | The specific problem of symbol recognition in graphical documents requires additional techniques to those developed for character recognition. The most well-known obstacle is the so-called Sayre paradox: Correct recognition requires good segmentation, yet improvement in segmentation is achieved using information provided by the recognition process. This dilemma can be avoided by techniques that identify sets of regions containing useful information. Such symbol-spotting methods allow the detection of symbols in maps or technical drawings without having to fully segment or fully recognize the entire content.
This unique text/reference provides a complete, integrated and large-scale solution to the challenge of designing a robust symbol-spotting method for collections of graphic-rich documents. The book examines a number of features and descriptors, from basic photometric descriptors commonly used in computer vision techniques to those specific to graphical shapes, presenting a methodology which can be used in a wide variety of applications. Additionally, readers are supplied with an insight into the problem of performance evaluation of spotting methods. Some very basic knowledge of pattern recognition, document image analysis and graphics recognition is assumed. |
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| 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  |
978-1-84996-208-7 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ RuL2010a | Serial | 1292 | ||
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| Author | Rain Eric Haamer; Eka Rusadze; Iiris Lusi; Tauseef Ahmed; Sergio Escalera; Gholamreza Anbarjafari | ||||
| Title | Review on Emotion Recognition Databases | Type | Book Chapter | ||
| Year | 2018 | Publication | Human-Robot Interaction: Theory and Application | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | emotion; computer vision; databases | ||||
| Abstract | Over the past few decades human-computer interaction has become more important in our daily lives and research has developed in many directions: memory research, depression detection, and behavioural deficiency detection, lie detection, (hidden) emotion recognition etc. Because of that, the number of generic emotion and face databases or those tailored to specific needs have grown immensely large. Thus, a comprehensive yet compact guide is needed to help researchers find the most suitable database and understand what types of databases already exist. In this paper, different elicitation methods are discussed and the databases are primarily organized into neat and informative tables based on the format. | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN |
978-1-78923-316-2 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | HUPBA; 602.133 | Approved | no | ||
| Call Number | Admin @ si @ HRL2018 | Serial | 3212 | ||
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| Author | Gholamreza Anbarjafari; Sergio Escalera | ||||
| Title | Human-Robot Interaction: Theory and Application | Type | Book Whole | ||
| Year | 2018 | Publication | Human-Robot Interaction: Theory and Application | Abbreviated Journal | |
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN |
978-1-78923-316-2 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | HUPBA | Approved | no | ||
| Call Number | Admin @ si @ AnE2018 | Serial | 3216 | ||
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| Author | Fadi Dornaika; Bogdan Raducanu | ||||
| Title | Subtle Facial Expression Recognition in Still Images and Videos | Type | Book Chapter | ||
| Year | 2011 | Publication | Advances in Face Image Analysis: Techniques and Technologies | Abbreviated Journal | |
| Volume | Issue | 14 | Pages | 259-277 | |
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| Abstract | This chapter addresses the recognition of basic facial expressions. It has three main contributions. First, the authors introduce a view- and texture independent schemes that exploits facial action parameters estimated by an appearance-based 3D face tracker. they represent the learned facial actions associated with different facial expressions by time series. Two dynamic recognition schemes are proposed: (1) the first is based on conditional predictive models and on an analysis-synthesis scheme, and (2) the second is based on examples allowing straightforward use of machine learning approaches. Second, the authors propose an efficient recognition scheme based on the detection of keyframes in videos. Third, the authors compare the dynamic scheme with a static one based on analyzing individual snapshots and show that in general the former performs better than the latter. The authors then provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). | ||||
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| Publisher | IGI-Global | Place of Publication | New York, USA | Editor | Yu-Jin Zhang |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN |
978-1-6152-0991-0 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ DoR2011 | Serial | 1751 | ||
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| Author | Maedeh Aghaei; Petia Radeva | ||||
| Title | Bag-of-Tracklets for Person Tracking in Life-Logging Data | Type | Conference Article | ||
| Year | 2014 | Publication | 17th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 269 | Issue | Pages | 35-44 | |
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| Abstract | By increasing popularity of wearable cameras, life-logging data analysis is becoming more and more important and useful to derive significant events out of this substantial collection of images. In this study, we introduce a new tracking method applied to visual life-logging, called bag-of-tracklets, which is based on detecting, localizing and tracking of people. Given the low spatial and temporal resolution of the image data, our model generates and groups tracklets in a unsupervised framework and extracts image sequences of person appearance according to a similarity score of the bag-of-tracklets. The model output is a meaningful sequence of events expressing human appearance and tracking them in life-logging data. The achieved results prove the robustness of our model in terms of efficiency and accuracy despite the low spatial and temporal resolution of the data. | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN |
978-1-61499-451-0 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @ AgR2015 | Serial | 2607 | ||
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| Author | Agata Lapedriza; David Masip; David Sanchez | ||||
| Title | Emotions Classification using Facial Action Units Recognition | Type | Conference Article | ||
| Year | 2014 | Publication | 17th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 269 | Issue | Pages | 55-64 | |
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| Abstract | In this work we build a system for automatic emotion classification from image sequences. We analyze subtle changes in facial expressions by detecting a subset of 12 representative facial action units (AUs). Then, we classify emotions based on the output of these AUs classifiers, i.e. the presence/absence of AUs. We base the AUs classification upon a set of spatio-temporal geometric and appearance features for facial representation, fusing them within the emotion classifier. A decision tree is trained for emotion classifying, making the resulting model easy to interpret by capturing the combination of AUs activation that lead to a particular emotion. For Cohn-Kanade database, the proposed system classifies 7 emotions with a mean accuracy of near 90%, attaining a similar recognition accuracy in comparison with non-interpretable models that are not based in AUs detection. | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN |
978-1-61499-451-0 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ LMS2014 | Serial | 2622 | ||
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| Author | Jaime Moreno; Xavier Otazu | ||||
| Title | Image compression algorithm based on Hilbert scanning of embedded quadTrees: an introduction of the Hi-SET coder | Type | Conference Article | ||
| Year | 2011 | Publication | IEEE International Conference on Multimedia and Expo | Abbreviated Journal | |
| Volume | Issue | Pages | 1-6 | ||
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| Abstract | In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. The implementation of the proposed coder is developed for gray-scale and color image compression. Hi-SET compressed images are, on average, 6.20dB better than the ones obtained by other compression techniques based on the Hilbert scanning. Moreover, Hi-SET improves the image quality in 1.39dB and 1.00dB in gray-scale and color compression, respectively, when compared with JPEG2000 coder. | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1945-7871 | ISBN |
978-1-61284-348-3 | Medium | |
| Area | Expedition | Conference | ICME | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ MoO2011a | Serial | 2176 | ||
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| Author | David Roche; Debora Gil; Jesus Giraldo | ||||
| Title | An inference model for analyzing termination conditions of Evolutionary Algorithms | Type | Conference Article | ||
| Year | 2011 | Publication | 14th Congrès Català en Intel·ligencia Artificial | Abbreviated Journal | |
| Volume | Issue | Pages | 216-225 | ||
| Keywords | Evolutionary Computation Convergence, Termination Conditions, Statistical Inference | ||||
| Abstract | In real-world problems, it is mandatory to design a termination condition for Evolutionary Algorithms (EAs) ensuring stabilization close to the unknown optimum. Distribution-based quantities are good candidates as far as suitable parameters are used. A main limitation for application to real-world problems is that such parameters strongly depend on the topology of the objective function, as well as, the EA paradigm used.
We claim that the termination problem would be fully solved if we had a model measuring to what extent a distribution-based quantity asymptotically behaves like the solution accuracy. We present a regression-prediction model that relates any two given quantities and reports if they can be statistically swapped as termination conditions. Our framework is applied to two issues. First, exploring if the parameters involved in the computation of distribution-based quantities influence their asymptotic behavior. Second, to what extent existing distribution-based quantities can be asymptotically exchanged for the accuracy of the EA solution. |
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| Address | Lleida, Catalonia (Spain) | ||||
| Corporate Author | Associació Catalana Intel·ligència Artificial | 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 |
978-1-60750-841-0 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ RGG2011a | Serial | 1677 | ||
| Permanent link to this record | |||||
| Author | Jorge Bernal; F. Javier Sanchez; Fernando Vilariño | ||||
| Title | Depth of Valleys Accumulation Algorithm for Object Detection | Type | Conference Article | ||
| Year | 2011 | Publication | 14th Congrès Català en Intel·ligencia Artificial | Abbreviated Journal | |
| Volume | 1 | Issue | 1 | Pages | 71-80 |
| Keywords | Object Recognition, Object Region Identification, Image Analysis, Image Processing | ||||
| Abstract | This work aims at detecting in which regions the objects in the image are by using information about the intensity of valleys, which appear to surround ob- jects in images where the source of light is in the line of direction than the camera. We present our depth of valleys accumulation method, which consists of two stages: first, the definition of the depth of valleys image which combines the output of a ridges and valleys detector with the morphological gradient to measure how deep is a point inside a valley and second, an algorithm that denotes points of the image as interior to objects those which are inside complete or incomplete boundaries in the depth of valleys image. To evaluate the performance of our method we have tested it on several application domains. Our results on object region identification are promising, specially in the field of polyp detection in colonoscopy videos, and we also show its applicability in different areas. | ||||
| Address | Lleida | ||||
| 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 |
978-1-60750-841-0 | Medium | ||
| Area | 800 | Expedition | Conference | CCIA | |
| Notes | MV;SIAI | Approved | no | ||
| Call Number | IAM @ iam @ BSV2011b | Serial | 1699 | ||
| Permanent link to this record | |||||
| Author | Xavier Perez Sala; Cecilio Angulo; Sergio Escalera | ||||
| Title | Biologically Inspired Turn Control in Robot Navigation | Type | Conference Article | ||
| Year | 2011 | Publication | 14th Congrès Català en Intel·ligencia Artificial | Abbreviated Journal | |
| Volume | Issue | Pages | 187-196 | ||
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| Abstract | An exportable and robust system for turn control using only camera images is proposed for path execution in robot navigation. Robot motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames in the image sequence. This information is used to compute the instantaneous rotation angle. Finally, control loop is closed correcting robot displacements when it is requested for a turn command. The proposed system has been successfully tested on the four-legged Sony Aibo robot. | ||||
| Address | Lleida | ||||
| 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 |
978-1-60750-841-0 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ PAE2011a | Serial | 1753 | ||
| Permanent link to this record | |||||
| Author | Eloi Puertas; Sergio Escalera; Oriol Pujol | ||||
| Title | Classifying Objects at Different Sizes with Multi-Scale Stacked Sequential Learning | Type | Conference Article | ||
| Year | 2010 | Publication | 13th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 220 | Issue | Pages | 193–200 | |
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| Abstract | Sequential learning is that discipline of machine learning that deals with dependent data. In this paper, we use the Multi-scale Stacked Sequential Learning approach (MSSL) to solve the task of pixel-wise classification based on contextual information. The main contribution of this work is a shifting technique applied during the testing phase that makes possible, thanks to template images, to classify objects at different sizes. The results show that the proposed method robustly classifies such objects capturing their spatial relationships. | ||||
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| Publisher | Place of Publication | Editor | R. Alquezar, A. Moreno, J. Aguilar | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN |
978-1-60750-642-3 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | HUPBA;MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ PEP2010 | Serial | 1448 | ||
| Permanent link to this record | |||||
| Author | Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva | ||||
| Title | Text Detection in Urban Scenes (video sample) | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 202 | Issue | Pages | 35–44 | |
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| Abstract | Abstract. Text detection in urban scenes is a hard task due to the high variability of text appearance: different text fonts, changes in the point of view, or partial occlusion are just a few problems. Text detection can be specially suited for georeferencing business, navigation, tourist assistance, or to help visual impaired people. In this paper, we propose a general methodology to deal with the problem of text detection in outdoor scenes. The method is based on learning spatial information of gradient based features and Census Transform images using a cascade of classifiers. The method is applied in the context of Mobile Mapping systems, where a mobile vehicle captures urban image sequences. Moreover, a cover data set is presented and tested with the new methodology. The results show high accuracy when detecting multi-linear text regions with high variability of appearance, at same time that it preserves a low false alarm rate compared to classical approaches | ||||
| Address | Cardona (Spain) | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN |
978-1-60750-061-2 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | OR;MILAB;HuPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EBV2009 | Serial | 1181 | ||
| Permanent link to this record | |||||
| Author | Sergio Escalera; Oriol Pujol; Petia Radeva; Jordi Vitria | ||||
| Title | Measuring Interest of Human Dyadic Interactions | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 202 | Issue | Pages | 45-54 | |
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| Abstract | In this paper, we argue that only using behavioural motion information, we are able to predict the interest of observers when looking at face-to-face interactions. We propose a set of movement-related features from body, face, and mouth activity in order to define a set of higher level interaction features, such as stress, activity, speaking engagement, and corporal engagement. Error-Correcting Output Codes framework with an Adaboost base classifier is used to learn to rank the perceived observer's interest in face-to-face interactions. The automatic system shows good correlation between the automatic categorization results and the manual ranking made by the observers. In particular, the learning system shows that stress features have a high predictive power for ranking interest of observers when looking at of face-to-face interactions. | ||||
| Address | Cardona (Spain) | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN |
978-1-60750-061-2 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | OR;MILAB;HuPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPR2009b | Serial | 1182 | ||
| Permanent link to this record | |||||
| Author | Xavier Baro; Sergio Escalera; Petia Radeva; Jordi Vitria | ||||
| Title | Generic Object Recognition in Urban Image Databases | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 202 | Issue | Pages | 27-34 | |
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| Abstract | In this paper we propose the construction of a visual content layer which describes the visual appearance of geographic locations in a city. We captured, by means of a Mobile Mapping system, a huge set of georeferenced images (>500K) which cover the whole city of Barcelona. For each image, hundreds of region descriptions are computed off-line and described as a hash code. All this information is extracted without an object of reference, which allows to search for any type of objects using their visual appearance. A new Visual Content layer is built over Google Maps, allowing the object recognition information to be organized and fused with other content, like satellite images, street maps, and business locations. | ||||
| Address | Cardona (Spain) | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN |
978-1-60750-061-2 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | OR;MILAB;HuPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ VER2009 | Serial | 1183 | ||
| Permanent link to this record | |||||
| Author | Francesco Ciompi; Oriol Pujol; Oriol Rodriguez-Leor; Angel Serrano; J. Mauri; Petia Radeva | ||||
| Title | On in-vitro and in-vivo IVUS data fusion | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 202 | Issue | Pages | 147-156 | |
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| Abstract | The design and the validation of an automatic plaque characterization technique based on Intravascular Ultrasound (IVUS) usually requires a data ground-truth. The histological analysis of post-mortem coronary arteries is commonly assumed as the state-of-the-art process for the extraction of a reliable data-set of atherosclerotic plaques. Unfortunately, the amount of data provided by this technique is usually few, due to the difficulties in collecting post-mortem cases and phenomena of tissue spoiling during histological analysis. In this paper we tackle the process of fusing in-vivo and in-vitro IVUS data starting with the analysis of recently proposed approaches for the creation of an enhanced IVUS data-set; furthermore, we propose a new approach, named pLDS, based on semi-supervised learning with a data selection criterion. The enhanced data-set obtained by each one of the analyzed approaches is used to train a classifier for tissue characterization purposes. Finally, the discriminative power of each classifier is quantitatively assessed and compared by classifying a data-set of validated in-vitro IVUS data. | ||||
| Address | Cardona (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 |
978-1-60750-061-2 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ CPR2009d | Serial | 1204 | ||
| Permanent link to this record | |||||