| Records |
| Author |
Onur Ferhat; Arcadi Llanza; Fernando Vilariño |
Title  |
A Feature-Based Gaze Estimation Algorithm for Natural Light Scenarios |
Type |
Conference Article |
| Year |
2015 |
Publication |
Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 |
Abbreviated Journal |
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| Volume |
9117 |
Issue |
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Pages |
569-576 |
| Keywords |
Eye tracking; Gaze estimation; Natural light; Webcam |
| Abstract |
We present an eye tracking system that works with regular webcams. We base our work on open source CVC Eye Tracker [7] and we propose a number of improvements and a novel gaze estimation method. The new method uses features extracted from iris segmentation and it does not fall into the traditional categorization of appearance–based/model–based methods. Our experiments show that our approach reduces the gaze estimation errors by 34 % in the horizontal direction and by 12 % in the vertical direction compared to the baseline system. |
| Address |
Santiago de Compostela; June 2015 |
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| Publisher |
Springer International Publishing |
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LNCS |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-319-19389-2 |
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Conference |
IbPRIA |
| Notes |
MV;SIAI |
Approved |
no |
| Call Number |
Admin @ si @ FLV2015a |
Serial |
2646 |
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| Author |
Giuseppe De Gregorio; Sanket Biswas; Mohamed Ali Souibgui; Asma Bensalah; Josep Llados; Alicia Fornes; Angelo Marcelli |
| Title |
A Few Shot Multi-representation Approach for N-Gram Spotting in Historical Manuscripts |
Type |
Conference Article |
| Year |
2022 |
Publication |
Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition (ICFHR2022) |
Abbreviated Journal |
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| Volume |
13639 |
Issue |
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Pages |
3-12 |
| Keywords |
N-gram spotting; Few-shot learning; Multimodal understanding; Historical handwritten collections |
| Abstract |
Despite recent advances in automatic text recognition, the performance remains moderate when it comes to historical manuscripts. This is mainly because of the scarcity of available labelled data to train the data-hungry Handwritten Text Recognition (HTR) models. The Keyword Spotting System (KWS) provides a valid alternative to HTR due to the reduction in error rate, but it is usually limited to a closed reference vocabulary. In this paper, we propose a few-shot learning paradigm for spotting sequences of a few characters (N-gram) that requires a small amount of labelled training data. We exhibit that recognition of important n-grams could reduce the system’s dependency on vocabulary. In this case, an out-of-vocabulary (OOV) word in an input handwritten line image could be a sequence of n-grams that belong to the lexicon. An extensive experimental evaluation of our proposed multi-representation approach was carried out on a subset of Bentham’s historical manuscript collections to obtain some really promising results in this direction. |
| Address |
December 04 – 07, 2022; Hyderabad, India |
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LNCS |
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Conference |
ICFHR |
| Notes |
DAG; 600.121; 600.162; 602.230; 600.140 |
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no |
| Call Number |
Admin @ si @ GBS2022 |
Serial |
3733 |
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| Author |
Mohamed Ali Souibgui; Alicia Fornes; Y.Kessentini; C.Tudor |
| Title |
A Few-shot Learning Approach for Historical Encoded Manuscript Recognition |
Type |
Conference Article |
| Year |
2021 |
Publication |
25th International Conference on Pattern Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
5413-5420 |
| Keywords |
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| Abstract |
Encoded (or ciphered) manuscripts are a special type of historical documents that contain encrypted text. The automatic recognition of this kind of documents is challenging because: 1) the cipher alphabet changes from one document to another, 2) there is a lack of annotated corpus for training and 3) touching symbols make the symbol segmentation difficult and complex. To overcome these difficulties, we propose a novel method for handwritten ciphers recognition based on few-shot object detection. Our method first detects all symbols of a given alphabet in a line image, and then a decoding step maps the symbol similarity scores to the final sequence of transcribed symbols. By training on synthetic data, we show that the proposed architecture is able to recognize handwritten ciphers with unseen alphabets. In addition, if few labeled pages with the same alphabet are used for fine tuning, our method surpasses existing unsupervised and supervised HTR methods for ciphers recognition. |
| Address |
Virtual; January 2021 |
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Conference |
ICPR |
| Notes |
DAG; 600.121; 600.140 |
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no |
| Call Number |
Admin @ si @ SFK2021 |
Serial |
3449 |
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| Author |
Lluis Gomez; Dimosthenis Karatzas |
| Title |
A fine-grained approach to scene text script identification |
Type |
Conference Article |
| Year |
2016 |
Publication |
12th IAPR Workshop on Document Analysis Systems |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
192-197 |
| Keywords |
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| Abstract |
This paper focuses on the problem of script identification in unconstrained scenarios. Script identification is an important prerequisite to recognition, and an indispensable condition for automatic text understanding systems designed for multi-language environments. Although widely studied for document images and handwritten documents, it remains an almost unexplored territory for scene text images. We detail a novel method for script identification in natural images that combines convolutional features and the Naive-Bayes Nearest Neighbor classifier. The proposed framework efficiently exploits the discriminative power of small stroke-parts, in a fine-grained classification framework. In addition, we propose a new public benchmark dataset for the evaluation of joint text detection and script identification in natural scenes. Experiments done in this new dataset demonstrate that the proposed method yields state of the art results, while it generalizes well to different datasets and variable number of scripts. The evidence provided shows that multi-lingual scene text recognition in the wild is a viable proposition. Source code of the proposed method is made available online. |
| Address |
Santorini; Grecia; April 2016 |
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Conference |
DAS |
| Notes |
DAG; 601.197; 600.084 |
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no |
| Call Number |
Admin @ si @ GoK2016b |
Serial |
2863 |
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| Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva; Jordi Vitria |
| Title |
A First Approach to Activity Recognition Using Topic Models |
Type |
Conference Article |
| Year |
2009 |
Publication |
12th International Conference of the Catalan Association for Artificial Intelligence |
Abbreviated Journal |
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| Volume |
202 |
Issue |
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Pages |
74 - 82 |
| Keywords |
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| Abstract |
In this work, we present a first approach to activity patterns discovery by mean of topic models. Using motion data collected with a wearable device we prototype, TheBadge, we analyse raw accelerometer data using Latent Dirichlet Allocation (LDA), a particular instantiation of topic models. Results show that for particular values of the parameters necessary for applying LDA to a countinous dataset, good accuracies in activity classification can be achieved. |
| Address |
Cardona, Spain |
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Edition |
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ISBN |
978-1-60750-061-2 |
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Conference |
CCIA |
| Notes |
OR;MILAB;HuPBA;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ CPR2009e |
Serial |
1231 |
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| Author |
Antonio Clavelli; Dimosthenis Karatzas; Josep Llados |
| Title |
A framework for the assessment of text extraction algorithms on complex colour images |
Type |
Conference Article |
| Year |
2010 |
Publication |
9th IAPR International Workshop on Document Analysis Systems |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
19–26 |
| Keywords |
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| Abstract |
The availability of open, ground-truthed datasets and clear performance metrics is a crucial factor in the development of an application domain. The domain of colour text image analysis (real scenes, Web and spam images, scanned colour documents) has traditionally suffered from a lack of a comprehensive performance evaluation framework. Such a framework is extremely difficult to specify, and corresponding pixel-level accurate information tedious to define. In this paper we discuss the challenges and technical issues associated with developing such a framework. Then, we describe a complete framework for the evaluation of text extraction methods at multiple levels, provide a detailed ground-truth specification and present a case study on how this framework can be used in a real-life situation. |
| Address |
Boston; USA; |
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Edition |
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ISBN |
978-1-60558-773-8 |
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Conference |
DAS |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ CKL2010 |
Serial |
1432 |
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| Author |
Mohammad Ali Bagheri; Gang Hu; Qigang Gao; Sergio Escalera |
| Title |
A Framework of Multi-Classifier Fusion for Human Action Recognition |
Type |
Conference Article |
| Year |
2014 |
Publication |
22nd International Conference on Pattern Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1260 - 1265 |
| Keywords |
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| Abstract |
The performance of different action-recognition methods using skeleton joint locations have been recently studied by several computer vision researchers. However, the potential improvement in classification through classifier fusion by ensemble-based methods has remained unattended. In this work, we evaluate the performance of an ensemble of five action learning techniques, each performing the recognition task from a different perspective. The underlying rationale of the fusion approach is that different learners employ varying structures of input descriptors/features to be trained. These varying structures cannot be attached and used by a single learner. In addition, combining the outputs of several learners can reduce the risk of an unfortunate selection of a poorly performing learner. This leads to having a more robust and general-applicable framework. Also, we propose two simple, yet effective, action description techniques. In order to improve the recognition performance, a powerful combination strategy is utilized based on the Dempster-Shafer theory, which can effectively make use of diversity of base learners trained on different sources of information. The recognition results of the individual classifiers are compared with those obtained from fusing the classifiers' output, showing advanced performance of the proposed methodology. |
| Address |
Stockholm; Sweden; August 2014 |
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Edition |
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| ISSN |
1051-4651 |
ISBN |
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Conference |
ICPR |
| Notes |
HuPBA;MILAB |
Approved |
no |
| Call Number |
Admin @ si @ BHG2014 |
Serial |
2446 |
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| Author |
Muhammad Muzzamil Luqman; Josep Llados; Jean-Yves Ramel; Thierry Brouard |
| Title |
A Fuzzy-Interval Based Approach For Explicit Graph Embedding, Recognizing Patterns in Signals, Speech, Images and Video |
Type |
Conference Article |
| Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
Abbreviated Journal |
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| Volume |
6388 |
Issue |
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Pages |
93–98 |
| Keywords |
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| Abstract |
We present a new method for explicit graph embedding. Our algorithm extracts a feature vector for an undirected attributed graph. The proposed feature vector encodes details about the number of nodes, number of edges, node degrees, the attributes of nodes and the attributes of edges in the graph. The first two features are for the number of nodes and the number of edges. These are followed by w features for node degrees, m features for k node attributes and n features for l edge attributes — which represent the distribution of node degrees, node attribute values and edge attribute values, and are obtained by defining (in an unsupervised fashion), fuzzy-intervals over the list of node degrees, node attributes and edge attributes. Experimental results are provided for sample data of ICPR2010 contest GEPR. |
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Springer, Heidelberg |
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LNCS |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-17710-1 |
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Conference |
ICPR |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ LLR2010 |
Serial |
1459 |
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| Author |
Maria Vanrell; Jordi Vitria; Xavier Roca |
| Title |
A General Morphological Framework for Perceptual Texture Discrimination based on Granulometries. |
Type |
Conference Article |
| Year |
1993 |
Publication |
Technical Workshop on Mathematical Morphology and its Applications to Signal Processing. |
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| Address |
Barcelona |
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| Notes |
OR;ISE;CIC;MV |
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no |
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BCNPCL @ bcnpcl @ VVR1993 |
Serial |
154 |
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| Author |
Ariel Amato; Felipe Lumbreras; Angel Sappa |
| Title |
A General-purpose Crowdsourcing Platform for Mobile Devices |
Type |
Conference Article |
| Year |
2014 |
Publication |
9th International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
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| Volume |
3 |
Issue |
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Pages |
211-215 |
| Keywords |
Crowdsourcing Platform; Mobile Crowdsourcing |
| Abstract |
This paper presents details of a general purpose micro-task on-demand platform based on the crowdsourcing philosophy. This platform was specifically developed for mobile devices in order to exploit the strengths of such devices; namely: i) massivity, ii) ubiquity and iii) embedded sensors. The combined use of mobile platforms and the crowdsourcing model allows to tackle from the simplest to the most complex tasks. Users experience is the highlighted feature of this platform (this fact is extended to both task-proposer and tasksolver). Proper tools according with a specific task are provided to a task-solver in order to perform his/her job in a simpler, faster and appealing way. Moreover, a task can be easily submitted by just selecting predefined templates, which cover a wide range of possible applications. Examples of its usage in computer vision and computer games are provided illustrating the potentiality of the platform. |
| Address |
Lisboa; Portugal; January 2014 |
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Conference |
VISAPP |
| Notes |
ISE; ADAS; 600.054; 600.055; 600.076; 600.078 |
Approved |
no |
| Call Number |
Admin @ si @ ALS2014 |
Serial |
2478 |
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| Author |
Patricia Suarez; Angel Sappa |
| Title |
A Generative Model for Guided Thermal Image Super-Resolution |
Type |
Conference Article |
| Year |
2024 |
Publication |
19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications |
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This paper presents a novel approach for thermal super-resolution based on a fusion prior, low-resolution thermal image and H brightness channel of the corresponding visible spectrum image. The method combines bicubic interpolation of the ×8 scale target image with the brightness component. To enhance the guidance process, the original RGB image is converted to HSV, and the brightness channel is extracted. Bicubic interpolation is then applied to the low-resolution thermal image, resulting in a Bicubic-Brightness channel blend. This luminance-bicubic fusion is used as an input image to help the training process. With this fused image, the cyclic adversarial generative network obtains high-resolution thermal image results. Experimental evaluations show that the proposed approach significantly improves spatial resolution and pixel intensity levels compared to other state-of-the-art techniques, making it a promising method to obtain high-resolution thermal. |
| Address |
Roma; Italia; February 2024 |
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VISAPP |
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MSIAU |
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no |
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Admin @ si @ SuS2024 |
Serial |
4002 |
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| Author |
Hunor Laczko; Meysam Madadi; Sergio Escalera; Jordi Gonzalez |
| Title |
A Generative Multi-Resolution Pyramid and Normal-Conditioning 3D Cloth Draping |
Type |
Conference Article |
| Year |
2024 |
Publication |
Winter Conference on Applications of Computer Vision |
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Issue |
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Pages |
8709-8718 |
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| Abstract |
RGB cloth generation has been deeply studied in the related literature, however, 3D garment generation remains an open problem. In this paper, we build a conditional variational autoencoder for 3D garment generation and draping. We propose a pyramid network to add garment details progressively in a canonical space, i.e. unposing and unshaping the garments w.r.t. the body. We study conditioning the network on surface normal UV maps, as an intermediate representation, which is an easier problem to optimize than 3D coordinates. Our results on two public datasets, CLOTH3D and CAPE, show that our model is robust, controllable in terms of detail generation by the use of multi-resolution pyramids, and achieves state-of-the-art results that can highly generalize to unseen garments, poses, and shapes even when training with small amounts of data. |
| Address |
Waikoloa; Hawai; USA; January 2024 |
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Conference |
WACV |
| Notes |
ISE; HUPBA |
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no |
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Admin @ si @ LME2024 |
Serial |
3996 |
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| Author |
Adria Molina; Lluis Gomez; Oriol Ramos Terrades; Josep Llados |
| Title |
A Generic Image Retrieval Method for Date Estimation of Historical Document Collections |
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Conference Article |
| Year |
2022 |
Publication |
Document Analysis Systems.15th IAPR International Workshop, (DAS2022) |
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13237 |
Issue |
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Pages |
583–597 |
| Keywords |
Date estimation; Document retrieval; Image retrieval; Ranking loss; Smooth-nDCG |
| Abstract |
Date estimation of historical document images is a challenging problem, with several contributions in the literature that lack of the ability to generalize from one dataset to others. This paper presents a robust date estimation system based in a retrieval approach that generalizes well in front of heterogeneous collections. We use a ranking loss function named smooth-nDCG to train a Convolutional Neural Network that learns an ordination of documents for each problem. One of the main usages of the presented approach is as a tool for historical contextual retrieval. It means that scholars could perform comparative analysis of historical images from big datasets in terms of the period where they were produced. We provide experimental evaluation on different types of documents from real datasets of manuscript and newspaper images. |
| Address |
La Rochelle, France; May 22–25, 2022 |
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DAS |
| Notes |
DAG; 600.140; 600.121 |
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no |
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Admin @ si @ MGR2022 |
Serial |
3694 |
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| Author |
Agata Lapedriza; David Masip; Jordi Vitria |
| Title |
A Hierarchical Approach for Multi-task Logistic Regression |
Type |
Conference Article |
| Year |
2007 |
Publication |
3rd Iberian Conference on Pattern Recognition and Image Analysis |
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4478 |
Issue |
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258–265 |
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Girona (Spain) |
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J. Marti et al. |
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LNCS |
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IbPRIA |
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OR; MV |
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no |
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BCNPCL @ bcnpcl @ LMV2007a |
Serial |
902 |
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| Author |
Francesco Ciompi; Oriol Pujol; Carlo Gatta; Xavier Carrillo; J. Mauri; Petia Radeva |
| Title |
A Holistic Approach for the Detection of Media-Adventitia Border in IVUS |
Type |
Conference Article |
| Year |
2011 |
Publication |
14th International Conference on Medical Image Computing and Computer Assisted Intervention |
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6893 |
Issue |
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401-408 |
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In this paper we present a methodology for the automatic detection of media-adventitia border (MAb) in Intravascular Ultrasound. A robust computation of the MAb is achieved through a holistic approach where the position of the MAb with respect to other tissues of the vessel is used. A learned quality measure assures that the resulting MAb is optimal with respect to all other tissues. The mean distance error computed through a set of 140 images is 0.2164 (±0.1326) mm. |
| Address |
Toronto, Canada |
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Springer Berlin Heidelberg |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-23625-9 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
MICCAI |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ CPG2011 |
Serial |
1739 |
| Permanent link to this record |
