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Super-resolution of Sensinel-2 imagery using generative adversarial networks
(Multidisciplinary Digital Publishing Institute (MDPI), 2020-07-28)
Article
Open AccessSentinel-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
(Elsevier, 2020-10)
Article
Restricted access - publisher's policyIt 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
(2019-06-15)
Article
Open AccessMultiple 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
(2020-07-05)
Article
Restricted access - publisher's policyImage 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
(Elsevier, 2020-06)
Article
Open AccessThe 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
(2020-03-25)
Article
Open AccessNeAT 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
(Multidisciplinary Digital Publishing Institute (MDPI), 2020-05-20)
Article
Open AccessThis 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
(2019-03)
Article
Open AccessQuantification 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
(2019-08-17)
Article
Open AccessBackground 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
(2020-01-13)
Article
Restricted access - publisher's policyThe 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
(2019-08-01)
Article
Open AccessMagnetic 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
(2019-07-01)
Article
Restricted access - publisher's policyFruit 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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