Recent Submissions

  • Super-resolution of Sensinel-2 imagery using generative adversarial networks 

    Salgueiro Romero, Luis Fernando; Marcello, Javier; Vilaplana Besler, Verónica (Multidisciplinary Digital Publishing Institute (MDPI), 2020-07-28)
    Article
    Open Access
    Sentinel-2 satellites provide multi-spectral optical remote sensing images with four bands at 10 m of spatial resolution. These images, due to the open data distribution policy, are becoming an important resource for several ...
  • FuCiTNet: improving the generalization of deep learning networks by the fusion of learned class-inherent transformations 

    Rey-Arena, Manuel; Guirado, Emilio; Tabik, Siham; Ruiz Hidalgo, Javier (Elsevier, 2020-10)
    Article
    Restricted access - publisher's policy
    It is widely known that very small datasets produce overfitting in Deep Neural Networks (DNNs), i.e., the network becomes highly biased to the data it has been trained on. This issue is often alleviated using transfer ...
  • RVOS: end-to-end recurrent network for video object segmentation 

    Ventura Royo, Carles; Bellver, Míriam; Girbau Xalabarder, Andreu; Salvador Aguilera, Amaia; Marqués Acosta, Fernando; Giró Nieto, Xavier (2019-06-15)
    Article
    Open Access
    Multiple object video object segmentation is a challenging task, specially for the zero-shot case, when no object mask is given at the initial frame and the model has to find the objects to be segmented along the sequence. ...
  • Mask-guided sample selection for semi-supervised instance segmentation 

    Bellver Bueno, Míriam; Salvador Aguilera, Amaia; Torres Viñals, Jordi; Giró Nieto, Xavier (2020-07-05)
    Article
    Restricted access - publisher's policy
    Image segmentation methods are usually trained with pixel-level annotations, which require significant human effort to collect. Weakly-supervised pipelines are the most common solution to address this constraint because ...
  • Fuji-SfM dataset: a collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry 

    Gené Mola, Jordi; Sanz Cortiella, Ricardo; Rosell Polo, Joan Ramon; Morros Rubió, Josep Ramon; Ruiz Hidalgo, Javier; Vilaplana Besler, Verónica; Gregorio, Eduard (Elsevier, 2020-06)
    Article
    Open Access
    The present dataset contains colour images acquired in a commercial Fuji apple orchard (Malus domestica Borkh. cv. Fuji) to reconstruct the 3D model of 11 trees by using structure-from-motion (SfM) photogrammetry. The data ...
  • 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
    Open Access
    NeAT 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. ...
  • Geometric model and calibration method for a solid-state LiDAR 

    García Gómez, Pablo; Royo Royo, Santiago; Rodrigo Arcay, Noel; Casas Pla, Josep Ramon (Multidisciplinary Digital Publishing Institute (MDPI), 2020-05-20)
    Article
    Open Access
    This paper presents a novel calibration method for solid-state LiDAR devices based on a geometrical description of their scanning system, which has variable angular resolution. Determining this distortion across the entire ...
  • Standardized assessment of automatic segmentation of white matter hyperintensities; results of the WMH segmentation challenge 

    Kuijf, Hugo J.; Biesbroek, J. Matthijs; De Bresser, Jeroen; Casamitjana Díaz, Adrià; Vilaplana Besler, Verónica (2019-03)
    Article
    Open Access
    Quantification of white matter hyperintensities (WMH) of presumed vascular origin is of key importance in many neurological research studies. Advanced measurements are obtained from manual segmentations on brain MR images, ...
  • 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
    Open Access
    Background 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 ...
  • Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry 

    Gené Mola, Jordi; Sanz Cortiella, Ricardo; Rosell Polo, Joan Ramon; Morros Rubió, Josep Ramon; Ruiz Hidalgo, Javier; Vilaplana Besler, Verónica; Gregorio, Eduard (2020-01-13)
    Article
    Restricted access - publisher's policy
    The development of remote fruit detection systems able to identify and 3D locate fruits provides opportunities to improve the efficiency of agriculture management. Most of the current fruit detection systems are based on ...
  • Shared latent structures between imaging features and biomarkers in early stages of Alzheimer's disease: a predictive study 

    Casamitjana Díaz, Adrià; Petrone, Paula; Molinuevo, José Luis; Gispert, Juan Domingo; Vilaplana Besler, Verónica (2019-08-01)
    Article
    Open Access
    Magnetic resonance imaging (MRI) provides high resolution brain morphological information and is used as a biomarker in neurodegenerative diseases. Population studies of brain morphology often seek to identify pathological ...
  • 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
    Restricted access - publisher's policy
    Fruit 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 ...

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