| Records |
| Author |
Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Apostolos Antonacopoulos; Josep Llados |
| Title |
An interactive appearance-based document retrieval system for historical newspapers |
Type |
Conference Article |
| Year |
2013 |
Publication |
Proceedings of the International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
84-87 |
| Keywords |
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| Abstract |
In this paper we present a retrieval-based application aimed at assisting a user to semi-automatically segment an incoming flow of historical newspaper images by automatically detecting a particular type of pages based on their appearance. A visual descriptor is used to assess page similarity while a relevance feedback process allow refining the results iteratively. The application is tested on a large dataset of digitised historic newspapers. |
| Address |
Barcelona; February 2013 |
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VISAPP |
| Notes |
DAG; 600.056; 600.045; 605.203 |
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no |
| Call Number |
Admin @ si @ GRK2013a |
Serial |
2290 |
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| Author |
Albert Gordo |
| Title |
A Cyclic Page Layout Descriptor for Document Classification & Retrieval |
Type |
Report |
| Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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| Volume |
128 |
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Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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CIC;DAG |
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no |
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Admin @ si @ Gor2009 |
Serial |
2387 |
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| Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
| Title |
Embedding of Graphs with Discrete Attributes Via Label Frequencies |
Type |
Journal Article |
| Year |
2013 |
Publication |
International Journal of Pattern Recognition and Artificial Intelligence |
Abbreviated Journal |
IJPRAI |
| Volume |
27 |
Issue |
3 |
Pages |
1360002-1360029 |
| Keywords |
Discrete attributed graphs; graph embedding; graph classification |
| Abstract |
Graph-based representations of patterns are very flexible and powerful, but they are not easily processed due to the lack of learning algorithms in the domain of graphs. Embedding a graph into a vector space solves this problem since graphs are turned into feature vectors and thus all the statistical learning machinery becomes available for graph input patterns. In this work we present a new way of embedding discrete attributed graphs into vector spaces using node and edge label frequencies. The methodology is experimentally tested on graph classification problems, using patterns of different nature, and it is shown to be competitive to state-of-the-art classification algorithms for graphs, while being computationally much more efficient. |
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DAG |
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no |
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Admin @ si @ GVB2013 |
Serial |
2305 |
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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 |
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 |
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Issue |
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Pages |
385 - 390 |
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| 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. |
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ISBN |
978-0-7695-4992-7 |
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Conference |
ALICE |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
GCV2013 |
Serial |
2268 |
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| Author |
Jose Manuel Alvarez; Theo Gevers; Ferran Diego; Antonio Lopez |
| Title |
Road Geometry Classification by Adaptative Shape Models |
Type |
Journal Article |
| Year |
2013 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
Abbreviated Journal |
TITS |
| Volume |
14 |
Issue |
1 |
Pages |
459-468 |
| Keywords |
road detection |
| Abstract |
Vision-based road detection is important for different applications in transportation, such as autonomous driving, vehicle collision warning, and pedestrian crossing detection. Common approaches to road detection are based on low-level road appearance (e.g., color or texture) and neglect of the scene geometry and context. Hence, using only low-level features makes these algorithms highly depend on structured roads, road homogeneity, and lighting conditions. Therefore, the aim of this paper is to classify road geometries for road detection through the analysis of scene composition and temporal coherence. Road geometry classification is proposed by building corresponding models from training images containing prototypical road geometries. We propose adaptive shape models where spatial pyramids are steered by the inherent spatial structure of road images. To reduce the influence of lighting variations, invariant features are used. Large-scale experiments show that the proposed road geometry classifier yields a high recognition rate of 73.57% ± 13.1, clearly outperforming other state-of-the-art methods. Including road shape information improves road detection results over existing appearance-based methods. Finally, it is shown that invariant features and temporal information provide robustness against disturbing imaging conditions. |
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Edition |
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1524-9050 |
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| Notes |
ADAS;ISE |
Approved |
no |
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Admin @ si @ AGD2013;; ADAS @ adas @ |
Serial |
2269 |
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| Author |
Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner |
| Title |
Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation |
Type |
Conference Article |
| Year |
2011 |
Publication |
In Proceedings of the Sixth International Workshop on Digital Technologies in Cartographic Heritage |
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Conference |
CartoHerit |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ RRL2011b |
Serial |
1978 |
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| Author |
Jon Almazan; Alicia Fornes; Ernest Valveny |
| Title |
A non-rigid appearance model for shape description and recognition |
Type |
Journal Article |
| Year |
2012 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
45 |
Issue |
9 |
Pages |
3105--3113 |
| Keywords |
Shape recognition; Deformable models; Shape modeling; Hand-drawn recognition |
| Abstract |
In this paper we describe a framework to learn a model of shape variability in a set of patterns. The framework is based on the Active Appearance Model (AAM) and permits to combine shape deformations with appearance variability. We have used two modifications of the Blurred Shape Model (BSM) descriptor as basic shape and appearance features to learn the model. These modifications permit to overcome the rigidity of the original BSM, adapting it to the deformations of the shape to be represented. We have applied this framework to representation and classification of handwritten digits and symbols. We show that results of the proposed methodology outperform the original BSM approach. |
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| ISSN |
0031-3203 |
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| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ AFV2012 |
Serial |
1982 |
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| Author |
Jon Almazan; David Fernandez; Alicia Fornes; Josep Llados; Ernest Valveny |
| Title |
A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection |
Type |
Conference Article |
| Year |
2012 |
Publication |
13th International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
453-458 |
| Keywords |
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| Abstract |
In this paper we propose an approach for word spotting in handwritten document images. We state the problem from a focused retrieval perspective, i.e. locating instances of a query word in a large scale dataset of digitized manuscripts. We combine two approaches, namely one based on word segmentation and another one segmentation-free. The first approach uses a hashing strategy to coarsely prune word images that are unlikely to be instances of the query word. This process is fast but has a low precision due to the errors introduced in the segmentation step. The regions containing candidate words are sent to the second process based on a state of the art technique from the visual object detection field. This discriminative model represents the appearance of the query word and computes a similarity score. In this way we propose a coarse-to-fine approach achieving a compromise between efficiency and accuracy. The validation of the model is shown using a collection of old handwritten manuscripts. We appreciate a substantial improvement in terms of precision regarding the previous proposed method with a low computational cost increase. |
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ISBN |
978-1-4673-2262-1 |
Medium |
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Conference |
ICFHR |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ AFF2012 |
Serial |
1983 |
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| Author |
Jon Almazan; Albert Gordo; Alicia Fornes; Ernest Valveny |
| Title |
Efficient Exemplar Word Spotting |
Type |
Conference Article |
| Year |
2012 |
Publication |
23rd British Machine Vision Conference |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
67.1- 67.11 |
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| Abstract |
In this paper we propose an unsupervised segmentation-free method for word spotting in document images.
Documents are represented with a grid of HOG descriptors, and a sliding window approach is used to locate the document regions that are most similar to the query. We use the exemplar SVM framework to produce a better representation of the query in an unsupervised way. Finally, the document descriptors are precomputed and compressed with Product Quantization. This offers two advantages: first, a large number of documents can be kept in RAM memory at the same time. Second, the sliding window becomes significantly faster since distances between quantized HOG descriptors can be precomputed. Our results significantly outperform other segmentation-free methods in the literature, both in accuracy and in speed and memory usage. |
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ISBN |
1-901725-46-4 |
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Conference |
BMVC |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ AGF2012 |
Serial |
1984 |
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| Author |
Ferran Poveda; Enric Marti; Debora Gil; Francesc Carreras; Manel Ballester |
| Title |
Helical Structure of Ventricular Anatomy by Diffusion Tensor Cardiac MR Tractography |
Type |
Journal Article |
| Year |
2012 |
Publication |
Journal of American College of Cardiology |
Abbreviated Journal |
JACC |
| Volume |
5 |
Issue |
7 |
Pages |
754-755 |
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| Abstract |
It is widely accepted that myocardial fiber architecture plays a critical role in myocardial contractility and relaxation (1). However, there is a lack of consensus about the distribution of the myocardial fibers and their spatial arrangement in the left and right ventricles. An understanding of the cardiac architecture should benefit the ventricular functional assessment, left ventricular reconstructive surgery planning, or resynchronization therapy in heart failure. Researchers have proposed several conceptual models to describe the architecture of the heart, ranging from gross dissection to histological presentation. The cardiac mesh model (2) proposes that the myocytes are arranged longitudinally and radially change their angulation along the myocardial depth. By contrast, the helical ventricular myocardial model states that the ventricular myocardium is a continuous anatomical helical layout of myocardial fibers (1 |
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1936-878X |
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IAM |
Approved |
no |
| Call Number |
IAM @ iam @ PMG2012 |
Serial |
1985 |
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| Author |
Jose Carlos Rubio; Joan Serrat; Antonio Lopez; N. Paragios |
| Title |
Image Contextual Representation and Matching through Hierarchies and Higher Order Graphs |
Type |
Conference Article |
| Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
Abbreviated Journal |
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Issue |
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Pages |
2664 - 2667 |
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| Abstract |
We present a region matching algorithm which establishes correspondences between regions from two segmented images. An abstract graph-based representation conceals the image in a hierarchical graph, exploiting the scene properties at two levels. First, the similarity and spatial consistency of the image semantic objects is encoded in a graph of commute times. Second, the cluttered regions of the semantic objects are represented with a shape descriptor. Many-to-many matching of regions is specially challenging due to the instability of the segmentation under slight image changes, and we explicitly handle it through high order potentials. We demonstrate the matching approach applied to images of world famous buildings, captured under different conditions, showing the robustness of our method to large variations in illumination and viewpoint. |
| Address |
Tsukuba Science City, Japan |
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Edition |
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| ISSN |
1051-4651 |
ISBN |
978-1-4673-2216-4 |
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Conference |
ICPR |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ RSL2012a; |
Serial |
2032 |
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| Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
| Title |
Graph Embedding in Vector Spaces by Node Attribute Statistics |
Type |
Journal Article |
| Year |
2012 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
45 |
Issue |
9 |
Pages |
3072-3083 |
| Keywords |
Structural pattern recognition; Graph embedding; Data clustering; Graph classification |
| Abstract |
Graph-based representations are of broad use and applicability in pattern recognition. They exhibit, however, a major drawback with regards to the processing tools that are available in their domain. Graphembedding into vectorspaces is a growing field among the structural pattern recognition community which aims at providing a feature vector representation for every graph, and thus enables classical statistical learning machinery to be used on graph-based input patterns. In this work, we propose a novel embedding methodology for graphs with continuous nodeattributes and unattributed edges. The approach presented in this paper is based on statistics of the node labels and the edges between them, based on their similarity to a set of representatives. We specifically deal with an important issue of this methodology, namely, the selection of a suitable set of representatives. In an experimental evaluation, we empirically show the advantages of this novel approach in the context of different classification problems using several databases of graphs. |
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0031-3203 |
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DAG |
Approved |
no |
| Call Number |
Admin @ si @ GVB2012a |
Serial |
1992 |
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| Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
| Title |
Feature Selection on Node Statistics Based Embedding of Graphs |
Type |
Journal Article |
| Year |
2012 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
| Volume |
33 |
Issue |
15 |
Pages |
1980–1990 |
| Keywords |
Structural pattern recognition; Graph embedding; Feature ranking; PCA; Graph classification |
| Abstract |
Representing a graph with a feature vector is a common way of making statistical machine learning algorithms applicable to the domain of graphs. Such a transition from graphs to vectors is known as graphembedding. A key issue in graphembedding is to select a proper set of features in order to make the vectorial representation of graphs as strong and discriminative as possible. In this article, we propose features that are constructed out of frequencies of node label representatives. We first build a large set of features and then select the most discriminative ones according to different ranking criteria and feature transformation algorithms. On different classification tasks, we experimentally show that only a small significant subset of these features is needed to achieve the same classification rates as competing to state-of-the-art methods. |
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DAG |
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no |
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Admin @ si @ GVB2012b |
Serial |
1993 |
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| Author |
Michael Holte; Bhaskar Chakraborty; Jordi Gonzalez; Thomas B. Moeslund |
| Title |
A Local 3D Motion Descriptor for Multi-View Human Action Recognition from 4D Spatio-Temporal Interest Points |
Type |
Journal Article |
| Year |
2012 |
Publication |
IEEE Journal of Selected Topics in Signal Processing |
Abbreviated Journal |
J-STSP |
| Volume |
6 |
Issue |
5 |
Pages |
553-565 |
| Keywords |
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| Abstract |
In this paper, we address the problem of human action recognition in reconstructed 3-D data acquired by multi-camera systems. We contribute to this field by introducing a novel 3-D action recognition approach based on detection of 4-D (3-D space $+$ time) spatio-temporal interest points (STIPs) and local description of 3-D motion features. STIPs are detected in multi-view images and extended to 4-D using 3-D reconstructions of the actors and pixel-to-vertex correspondences of the multi-camera setup. Local 3-D motion descriptors, histogram of optical 3-D flow (HOF3D), are extracted from estimated 3-D optical flow in the neighborhood of each 4-D STIP and made view-invariant. The local HOF3D descriptors are divided using 3-D spatial pyramids to capture and improve the discrimination between arm- and leg-based actions. Based on these pyramids of HOF3D descriptors we build a bag-of-words (BoW) vocabulary of human actions, which is compressed and classified using agglomerative information bottleneck (AIB) and support vector machines (SVMs), respectively. Experiments on the publicly available i3DPost and IXMAS datasets show promising state-of-the-art results and validate the performance and view-invariance of the approach. |
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1932-4553 |
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ISE |
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no |
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Admin @ si @ HCG2012 |
Serial |
1994 |
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| Author |
Francesco Ciompi; Oriol Pujol; Carlo Gatta; Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva |
| Title |
HoliMab: A Holistic Approach for Media-Adventitia Border Detection in Intravascular Ultrasound |
Type |
Journal Article |
| Year |
2012 |
Publication |
Medical Image Analysis |
Abbreviated Journal |
MIA |
| Volume |
16 |
Issue |
6 |
Pages |
1085-1100 |
| Keywords |
Media–Adventitia border detection; Intravascular ultrasound; Multi-Scale Stacked Sequential Learning; Error-correcting output codes; Holistic segmentation |
| Abstract |
We present a fully automatic methodology for the detection of the Media-Adventitia border (MAb) in human coronary artery in Intravascular Ultrasound (IVUS) images. A robust border detection is achieved by means of a holistic interpretation of the detection problem where the target object, i.e. the media layer, is considered as part of the whole vessel in the image and all the relationships between tissues are learnt. A fairly general framework exploiting multi-class tissue characterization as well as contextual information on the morphology and the appearance of the tissues is presented. The methodology is (i) validated through an exhaustive comparison with both Inter-observer variability on two challenging databases and (ii) compared with state-of-the-art methods for the detection of the MAb in IVUS. The obtained averaged values for the mean radial distance and the percentage of area difference are 0.211 mm and 10.1%, respectively. The applicability of the proposed methodology to clinical practice is also discussed. |
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|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ CPG2012 |
Serial |
1995 |
| Permanent link to this record |
