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Author |
Carlo Gatta; Oriol Pujol; O. Rodriguez-Leor; J. Mauri; Petia Radeva |
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Title |
Robust Image-based IVUS Pullbacks Gating |
Type |
Book Chapter |
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Year |
2008 |
Publication |
Proceedings 11th International ConferenceMedical Image Computing and Computer–Assisted Intervention |
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Volume |
5242 |
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Pages |
518–525 |
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NY (USA) |
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MICCAI |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ GPR2008a |
Serial |
1037 |
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Author |
Carlo Gatta; Oriol Pujol; O. Rodriguez-Leor; Josefina Mauri; Petia Radeva |
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Title |
Improved Rigid Registration of Vessel Structures using the Fast Radial Symmetry Transform |
Type |
Conference Article |
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Year |
2008 |
Publication |
Computer Vision for Intravascular Imaging CVII’08 Workshop Medical Image Computing and Computer–Assisted Intervention , 11th International Conference |
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128–136 |
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NY (USA) |
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MICCAI |
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MILAB;HUPBA |
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no |
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Call Number |
BCNPCL @ bcnpcl @ GPR2008b |
Serial |
1038 |
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Author |
Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva |
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Title |
ECOC Random Fields for Lumen Segmentation in Radial Artery IVUS Sequences |
Type |
Conference Article |
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Year |
2009 |
Publication |
12th International Conference on Medical Image and Computer Assisted Intervention |
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Volume |
5762 |
Issue |
II |
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The measure of lumen volume on radial arteries can be used to evaluate the vessel response to different vasodilators. In this paper, we present a framework for automatic lumen segmentation in longitudinal cut images of radial artery from Intravascular ultrasound sequences. The segmentation is tackled as a classification problem where the contextual information is exploited by means of Conditional Random Fields (CRFs). A multi-class classification framework is proposed, and inference is achieved by combining binary CRFs according to the Error-Correcting-Output-Code technique. The results are validated against manually segmented sequences. Finally, the method is compared with other state-of-the-art classifiers. |
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London, UK |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-04270-6 |
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MICCAI |
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Notes |
MILAB;HuPBA |
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no |
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Call Number |
BCNPCL @ bcnpcl @ CPF2009 |
Serial |
1228 |
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Author |
Carlo Gatta; Simone Balocco; Francesco Ciompi; R. Hemetsberger; O. Rodriguez-Leor; Petia Radeva |
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Title |
Real-time gating of IVUS sequences based on motion blur analysis: Method and quantitative validation |
Type |
Conference Article |
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Year |
2010 |
Publication |
13th international conference on Medical image computing and computer-assisted intervention |
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Volume |
II |
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Pages |
59-67 |
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Abstract |
Intravascular Ultrasound (IVUS) is an image-guiding technique for cardiovascular diagnostic, providing cross-sectional images of vessels. During the acquisition, the catheter is pulled back (pullback) at a constant speed in order to acquire spatially subsequent images of the artery. However, during this procedure, the heart twist produces a swinging fluctuation of the probe position along the vessel axis. In this paper we propose a real-time gating algorithm based on the analysis of motion blur variations during the IVUS sequence. Quantitative tests performed on an in-vitro ground truth data base shown that our method is superior to state of the art algorithms both in computational speed and accuracy. |
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Springer-Verlag Berlin |
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MICCAI |
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MILAB |
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no |
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Call Number |
BCNPCL @ bcnpcl @ GBC2010 |
Serial |
1447 |
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Author |
Francesco Ciompi; Oriol Pujol; Carlo Gatta; Xavier Carrillo; Josepa Mauri; Petia Radeva |
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Title |
A Holistic Approach for the Detection of Media-Adventitia Border in IVUS |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th International Conference on Medical Image Computing and Computer Assisted Intervention |
Abbreviated Journal |
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Volume |
6893 |
Issue |
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Pages |
401-408 |
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Abstract |
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. |
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Address |
Toronto, Canada |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-23625-9 |
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MICCAI |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ CPG2011 |
Serial |
1739 |
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Permanent link to this record |
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Author |
Antonio Hernandez; Carlo Gatta; Sergio Escalera; Laura Igual; Victoria Martin Yuste; Petia Radeva |
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Title |
Accurate and Robust Fully-Automatic QCA: Method and Numerical Validation |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th International Conference on Medical Image Computing and Computer Assisted Intervention |
Abbreviated Journal |
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Volume |
14 |
Issue |
3 |
Pages |
496-503 |
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Abstract |
The Quantitative Coronary Angiography (QCA) is a methodology used to evaluate the arterial diseases and, in particular, the degree of stenosis. In this paper we propose AQCA, a fully automatic method for vessel segmentation based on graph cut theory. Vesselness, geodesic paths and a new multi-scale edgeness map are used to compute a globally optimal artery segmentation. We evaluate the method performance in a rigorous numerical way on two datasets. The method can detect an artery with precision 92.9 +/- 5% and sensitivity 94.2 +/- 6%. The average absolute distance error between detected and ground truth centerline is 1.13 +/- 0.11 pixels (about 0.27 +/- 0.025 mm) and the absolute relative error in the vessel caliber estimation is 2.93% with almost no bias. Moreover, the method can discriminate between arteries and catheter with an accuracy of 96.4%. |
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Toronto, Canada |
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Springer |
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978-3-642-23625-9 |
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MICCAI |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ HGE2011 |
Serial |
1769 |
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Permanent link to this record |
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Author |
Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil |
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Title |
Volumetric Anatomical Parameterization and Meshing for Inter-patient Liver Coordinate System Deffinition |
Type |
Conference Article |
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Year |
2013 |
Publication |
16th International Conference on Medical Image Computing and Computer Assisted Intervention |
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Address |
Nagoya; Japan; September 2013 |
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MICCAI |
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IAM |
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no |
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Call Number |
Admin @ si @ VGG2013 |
Serial |
2301 |
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Author |
Francesco Ciompi; Simone Balocco; Carles Caus; Josepa Mauri; Petia Radeva |
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Title |
Stent shape estimation through a comprehensive interpretation of intravascular ultrasound images |
Type |
Conference Article |
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Year |
2013 |
Publication |
16th International Conference on Medical Image Computing and Computer Assisted Intervention |
Abbreviated Journal |
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Volume |
8150 |
Issue |
2 |
Pages |
345-352 |
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Abstract |
We present a method for automatic struts detection and stent shape estimation in cross-sectional intravascular ultrasound images. A stent shape is first estimated through a comprehensive interpretation of the vessel morphology, performed using a supervised context-aware multi-class classification scheme. Then, the successive strut identification exploits both local appearance and the defined stent shape. The method is tested on 589 images obtained from 80 patients, achieving a F-measure of 74.1% and an averaged distance between manual and automatic struts of 0.10 mm. |
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Address |
Nagoya; Japan; September 2013 |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
ISBN |
978-3-642-40762-8 |
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MICCAI |
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MILAB |
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no |
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Call Number |
Admin @ si @ CBC2013 |
Serial |
2258 |
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Author |
Marina Alberti; Simone Balocco; Xavier Carrillo; Josepa Mauri; Petia Radeva |
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Title |
Automatic Non-Rigid Temporal Alignment of IVUS Sequences |
Type |
Conference Article |
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Year |
2012 |
Publication |
15th International Conference on Medical Image Computing and Computer Assisted Intervention |
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Volume |
1 |
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642-650 |
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Clinical studies on atherosclerosis regression/progression performed by Intravascular Ultrasound analysis require the alignment of pullbacks of the same patient before and after clinical interventions. In this paper, a methodology for the automatic alignment of IVUS sequences based on the Dynamic Time Warping technique is proposed. The method is adapted to the specific IVUS alignment task by applying the non-rigid alignment technique to multidimensional morphological signals, and by introducing a sliding window approach together with a regularization term. To show the effectiveness of our method, an extensive validation is performed both on synthetic data and in-vivo IVUS sequences. The proposed method is robust to stent deployment and post dilation surgery and reaches an alignment error of approximately 0.7 mm for in-vivo data, which is comparable to the inter-observer variability. |
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Address |
Nice, France |
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Springer-Verlag Berlin, Heidelberg |
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978-3-642-33414-6 |
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MICCAI |
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MILAB |
Approved |
no |
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Call Number |
Admin @ si @ ABC2012 |
Serial |
2168 |
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Author |
Md.Mostafa Kamal Sarker; , Hatem A. Rashwan; Farhan Akram; Syeda Furruka Banu; Adel Saleh; Vivek Kumar Singh; Forhad U. H. Chowdhury; Saddam Abdulwahab; Santiago Romani; Petia Radeva; Domenec Puig |
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Title |
SLSDeep: Skin Lesion Segmentation Based on Dilated Residual and Pyramid Pooling Networks. |
Type |
Conference Article |
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Year |
2018 |
Publication |
21st International Conference on Medical Image Computing & Computer Assisted Intervention |
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Volume |
2 |
Issue |
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Pages |
21-29 |
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Abstract |
Skin lesion segmentation (SLS) in dermoscopic images is a crucial task for automated diagnosis of melanoma. In this paper, we present a robust deep learning SLS model, so-called SLSDeep, which is represented as an encoder-decoder network. The encoder network is constructed by dilated residual layers, in turn, a pyramid pooling network followed by three convolution layers is used for the decoder. Unlike the traditional methods employing a cross-entropy loss, we investigated a loss function by combining both Negative Log Likelihood (NLL) and End Point Error (EPE) to accurately segment the melanoma regions with sharp boundaries. The robustness of the proposed model was evaluated on two public databases: ISBI 2016 and 2017 for skin lesion analysis towards melanoma detection challenge. The proposed model outperforms the state-of-the-art methods in terms of segmentation accuracy. Moreover, it is capable to segment more than 100 images of size 384x384 per second on a recent GPU. |
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Granada; Espanya; September 2018 |
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MICCAI |
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Notes |
MILAB; no proj |
Approved |
no |
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Call Number |
Admin @ si @ SRA2018 |
Serial |
3112 |
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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Current Challenges on Polyp Detection in Colonoscopy Videos: From Region Segmentation to Region Classification. a Pattern Recognition-based Approach.ased Approach |
Type |
Conference Article |
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Year |
2011 |
Publication |
2nd International Workshop on Medical Image Analysis and Descriptionfor Diagnosis Systems |
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62-71 |
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Medical Imaging, Colonoscopy, Pattern Recognition, Segmentation, Polyp Detection, Region Description, Machine Learning, Real-time. |
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Abstract |
In this paper we present our approach on real-time polyp detection in colonoscopy videos. Our method consists of three stages: Image Segmentation, Region Description and Image Classification. Taking into account the constraints of our project, we introduce our segmentation system that is based on the model of appearance of the polyp that we have defined after observing real videos from colonoscopy processes. The output of this stage will ideally be a low number of regions of which one of them should cover the whole polyp region (if there is one in the image). This regions will be described in terms of features and, as a result of a machine learning schema, classified based on the values that they have for the several features that we will use on their description. Although we are still on the early stages of the project, we present some preliminary segmentation results that indicates that we are going in a good direction. |
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Rome, Italy |
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SciTePress |
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Djemal, Khalifa |
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800 |
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MIAD |
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Notes |
MV;SIAI |
Approved |
no |
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Call Number |
IAM @ iam @ BSV2011a |
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1695 |
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Author |
Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate |
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Title |
Is there a pattern of Chromosome territoriality along mice spermatogenesis? |
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Conference Article |
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2017 |
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3rd Spanish MeioNet Meeting Abstract Book |
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55-56 |
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Miraflores de la Sierra; Madrid; June 2017 |
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MEIONET |
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IAM; 600.096; 600.145 |
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no |
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Admin @ si @ |
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2958 |
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Author |
Mohamed Ali Souibgui; Y.Kessentini; Alicia Fornes |
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Title |
A conditional GAN based approach for distorted camera captured documents recovery |
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Conference Article |
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2020 |
Publication |
4th Mediterranean Conference on Pattern Recognition and Artificial Intelligence |
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Virtual; December 2020 |
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MedPRAI |
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DAG; 600.121 |
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no |
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Admin @ si @ SKF2020 |
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3450 |
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Author |
Aniol Lidon; Xavier Giro; Marc Bolaños; Petia Radeva; Markus Seidl; Matthias Zeppelzauer |
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Title |
UPC-UB-STP @ MediaEval 2015 diversity task: iterative reranking of relevant images |
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Conference Article |
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2015 |
Publication |
2015 MediaEval Retrieving Diverse Images Task |
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This paper presents the results of the UPC-UB-STP team in the 2015 MediaEval Retrieving Diverse Images Task. The goal of the challenge is to provide a ranked list of Flickr photos for a predefined set of queries. Our approach firstly generates a ranking of images based on a query-independent estimation of its relevance. Only top results are kept and iteratively re-ranked based on their intra-similarity to introduce diversity. |
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Wurzen; Germany; September 2015 |
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MediaEval |
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MILAB |
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Admin @ si @LGB2016 |
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2793 |
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Author |
Laura Lopez-Fuentes; Joost Van de Weijer; Marc Bolaños; Harald Skinnemoen |
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Title |
Multi-modal Deep Learning Approach for Flood Detection |
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Conference Article |
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2017 |
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MediaEval Benchmarking Initiative for Multimedia Evaluation |
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In this paper we propose a multi-modal deep learning approach to detect floods in social media posts. Social media posts normally contain some metadata and/or visual information, therefore in order to detect the floods we use this information. The model is based on a Convolutional Neural Network which extracts the visual features and a bidirectional Long Short-Term Memory network to extract the semantic features from the textual metadata. We validate the
method on images extracted from Flickr which contain both visual information and metadata and compare the results when using both, visual information only or metadata only. This work has been done in the context of the MediaEval Multimedia Satellite Task. |
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Dublin; Ireland; September 2017 |
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MediaEval |
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Notes |
LAMP; 600.084; 600.109; 600.120 |
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no |
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Call Number |
Admin @ si @ LWB2017a |
Serial |
2974 |
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