Exploració per autor "Vilaplana Besler, Verónica"
Ara es mostren els items 54-73 de 143
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Leishmaniasis parasite segmentation and classification using deep learning
Górriz, Marc; Aparicio, Albert; Raventós, Berta; Vilaplana Besler, Verónica; Sayrol Clols, Elisa; López Codina, Daniel (Springer, 2018)
Comunicació de congrés
Accés restringit per política de l'editorialLeishmaniasis is considered a neglected disease that causes thousands of deaths annually in some tropical and subtropical countries. There are various techniques to diagnose leishmaniasis of which manual microscopy is ... -
Looking behind occlusions: a study on amodal segmentation for robust on-tree apple fruit size estimation
Gené-Mola, Jordi; Ferrer Ferrer, Mar; Gregorio López, Eduard; Blok, Pieter; Hemming, Jochen; Morros Rubió, Josep Ramon; Rosell Polo, Joan R.; Vilaplana Besler, Verónica; Ruiz Hidalgo, Javier (2023-06)
Article
Accés obertThe detection and sizing of fruits with computer vision methods is of interest because it provides relevant information to improve the management of orchard farming. However, the presence of partially occluded fruits limits ... -
Machine learning on combined neuroimaging and plasma biomarkers for triaging participants of secondary prevention trials in Alzheimer’s disease
Cumplido Mayoral, Irene; Salvado, Gemma; Shekari, Mahnaz; Operto, Grégory; Falcón, Carles; Milà Alomà, Marta; Niñerola Baizán, Aida; Molinuevo Guix, José Luis; Zetterberg, Henrik; Blennow, Kaj; Suarez-Calvet, Marc; Vilaplana Besler, Verónica; Gispert López, Juan Domingo (Wiley, 2021-12)
Article
Accés obertBackground: Plasma biomarkers have demonstrated excellent agreement with established markers of amyloid-ß (Aß) positivity (PET and CSF) to identify patients with symptomatic AD. However, their predictive capacity in ... -
Magnetic resonance imaging and machine learning make a valuable combined tool for the screening of preclinical AD
Petrone, Paula; Vilaplana Besler, Verónica; Casamitjana Díaz, Adrià; Domingo Gispert, Juan; Molinuevo, Jose Luis; Sánchez Escobedo, Dalila (2017-07)
Article
Accés obert -
Masked V-Net: an approach to brain tumor segmentation
Catà, Marcel; Casamitjana Díaz, Adrià; Sanchez Muriana, Irina; Combalia, Marc; Vilaplana Besler, Verónica (2017)
Comunicació de congrés
Accés restringit per política de l'editorialThis paper introduces Masked V-Net architecture, a variant of the recently introduced V-Net[13] that reformulates the residual connections and uses a ROI mask to constrain the network to train only on relevant voxels. ... -
Materials transversals per a l'aprenentatge actiu de les matèries de processat d'imatge i vídeo
Morros Rubió, Josep Ramon; Vilaplana Besler, Verónica; Ruiz Hidalgo, Javier; Casas Pla, Josep Ramon; Gasull Llampallas, Antoni; Marqués Acosta, Fernando; Pardàs Feliu, Montse; Salembier Clairon, Philippe Jean (2014)
Text en actes de congrés
Accés obertAquest treball vol promoure la col·laboració i coordinació entre assignatures de processat d'imatge/vídeo amb l’objectiu de potenciar els resultats en l'aprenentatge. Les principals contribucions son a) la creació d’un ... -
Measuring traffic lane-changing by converting video into space–time still images
Sala Sanmartí, Marcel; Soriguera Martí, Francesc; Huillca, Kevin; Vilaplana Besler, Verónica (2019-06)
Article
Accés obertEmpirical data is needed in order to extend our knowledge of traffic behavior. Video recordings are used to enrich typical data from loop detectors. In this context, data extraction from videos becomes a challenging task. ... -
Monte-Carlo sampling applied to multiple instance learning for histological image classification
Combalia, Marc; Vilaplana Besler, Verónica (Springer, 2018)
Comunicació de congrés
Accés restringit per política de l'editorialWe propose a patch sampling strategy based on a sequential Monte-Carlo method for high resolution image classification in the context of Multiple Instance Learning. When compared with grid sampling and uniform sampling ... -
Monte-Carlo sampling applied to multiple instance learning for whole slide image classification
Combalia, Marc; Vilaplana Besler, Verónica (2018)
Comunicació de congrés
Accés obertIn this paper we propose a patch sampling strategy based on sequential Monte-Carlo methods for Whole Slide Image classification in the context of Multiple Instance Learning and show its capability to achieve high generalization ... -
MRI brain tumor segmentation and uncertainty estimation using 3D-UNet architectures
Mora Ballestar, Laura; Vilaplana Besler, Verónica (Springer Nature, 2021)
Capítol de llibre
Accés obertAutomation of brain tumor segmentation in 3D magnetic resonance images (MRIs) is key to assess the diagnostic and treatment of the disease. In recent years, convolutional neural networks (CNNs) have shown improved results ... -
MRI-based screening of preclinical Alzheimer's disease for prevention clinical trials
Casamitjana Díaz, Adrià; Petrone, Paula; Tucholka, Alan; Falcón, Carlos; Skouras, Stavros; Molinuevo, José Luis; Vilaplana Besler, Verónica; Gispert, Juan Domingo (IOS Press, 2018)
Article
Accés obertThe identification of healthy individuals harboring amyloid pathology represents one important challenge for secondary prevention clinical trials in Alzheimer’s disease (AD). Consequently, noninvasive and cost-efficient ... -
Multi-modal deep learning for Fuji apple detection using RGB-D cameras and their radiometric capabilities
Gené Mola, Jordi; Vilaplana Besler, Verónica; Rosell Polo, Joan Ramon; Morros Rubió, Josep Ramon; Ruiz Hidalgo, Javier; Gregorio, Eduard (2019-07-01)
Article
Accés obertFruit detection and localization will be essential for future agronomic management of fruit crops, with applications in yield prediction, yield mapping and automated harvesting. RGB-D cameras are promising sensors for fruit ... -
MULTIMEDIA CODING (Examen 2n quadrimestre, 1r parcial)
Vilaplana Besler, Verónica; Morros Rubió, Josep Ramon; Ruiz Hidalgo, Javier; Esquerra Llucià, Ignasi (Universitat Politècnica de Catalunya, 2012-04-18)
Examen
Accés restringit a la comunitat UPC -
MULTIMEDIA CODING (Examen 2n quadrimestre, 2n parcial)
Esquerra Llucià, Ignasi; Morros Rubió, Josep Ramon; Ruiz Hidalgo, Javier; Vilaplana Besler, Verónica (Universitat Politècnica de Catalunya, 2012-06-11)
Examen
Accés restringit a la comunitat UPC -
Multiresolution co-clustering for uncalibrated multiview segmentation
Ventura, Carles; Varas, David; Vilaplana Besler, Verónica; Giró Nieto, Xavier; Marqués Acosta, Fernando (2019-05-04)
Article
Accés obertWe propose a technique for coherently co-clustering uncalibrated views of a scene with a contour-based representation. Our work extends the previous framework, an iterative algorithm for segmenting sequences with small ... -
NeAT: a nonlinear analysis toolbox for neuroimaging
Casamitjana Díaz, Adrià; Vilaplana Besler, Verónica; Puch Giner, Santi; Aduriz Saiz, Asier; Operto, Grégory; Cacciaglia, Raffaele; Falcón, Carlos; Molinuevo, José Luis; Gispert, Juan Domingo; López Molina, Carlos Alejandro (2020-03-25)
Article
Accés obertNeAT is a modular, flexible and user-friendly neuroimaging analysis toolbox for modeling linear and nonlinear effects overcoming the limitations of the standard neuroimaging methods which are solely based on linear models. ... -
Object detection and segmentation on a hierarchical region-based image representation
Vilaplana Besler, Verónica; Marqués Acosta, Fernando; León Cristóbal, Míriam; Gasull Llampallas, Antoni (2010)
Comunicació de congrés
Accés obertIn this paper we present a general framework for object detection and segmentation. Using a bottom-up unsupervised merging algorithm, a region-based hierarchy that represents the image at different resolution levels is ... -
Picking groups instead of samples: a close look at Static Pool-based Meta-Active Learning
Mas Méndez, Ignasi; Morros Rubió, Josep Ramon; Vilaplana Besler, Verónica (Institute of Electrical and Electronics Engineers (IEEE), 2019)
Comunicació de congrés
Accés obertActive Learning techniques are used to tackle learning problems where obtaining training labels is costly. In this work we use Meta-Active Learning to learn to select a subset of samples from a pool of unsupervised input ... -
Prediction of amyloid pathology in cognitively unimpaired individuals using structural MRI
Cumplido Mayoral, Irene; Ingala, Silvia; Lorenzini, Luigi; Wink, Alle Meije; Haller, Sven; Molinuevo Guix, Jose Luis; Wolz, Robin; Palombit, Alessandro; Schwarz, Adam J.; Vilaplana Besler, Verónica (Wiley, 2021-12)
Article
Accés obertBackground: Structural MRI measurements can contribute to the prediction of amyloid pathology in cognitively unimpaired (CU) individuals. In this work, we aimed at studying the predictive capacity, robustness, and ... -
Prediction of amyloid pathology in cognitively unimpaired individuals using voxel-wise analysis of longitudinal structural brain MRI
Petrone, Paula; Casamitjana Díaz, Adrià; Falcón, Carlos; Artigues, Miquel; Operto, Grégory; Cacciaglia, Raffaele; Molinuevo, José Luis; Vilaplana Besler, Verónica; Gispert, Juan Domingo (2019-08-17)
Article
Accés obertBackground Magnetic resonance imaging (MRI) has unveiled specific alterations at different stages of Alzheimer’s disease (AD) pathophysiologic continuum constituting what has been established as “AD signature”. To what ...