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2D–3D geometric fusion network using multi-neighbourhood graph convolution for RGB-D indoor scene classification
(Elsevier, 2021-12)
Article
Restricted access - publisher's policyMulti-modal fusion has been proved to help enhance the performance of scene classification tasks. This paper presents a 2D-3D Fusion stage that combines 3D Geometric Features with 2D Texture Features obtained by 2D ... -
Advanced processing of multiplatform remote sensing imagery for the monitoring of coastal and mountain ecosystems
(Institute of Electrical and Electronics Engineers (IEEE), 2021)
Article
Open AccessCoastal areas are key to sustaining biodiversity, but their complexity and variability makes their analysis challenging. On the other hand, mountain ecosystems include a large percentage of the global biodiversity and their ... -
Mixed integration of CDIO skills into telecommunication engineering curricula
(2010)
Article
Open AccessSpain has been intensively involved in designing engineering curricula for the last two years and next academic year all engineering schools will be deploying all bachelor programs adapted to the EHEA and to the Spanish ... -
Projection to latent spaces disentangles pathological effects on brain morphology in the asymptomatic phase of Alzheimer's disease
(2020-07-28)
Article
Open AccessAlzheimer's disease (AD) continuum is defined as a cascade of several neuropathological processes that can be measured using biomarkers, such as cerebrospinal fluid (CSF) levels of Aß, p-tau, and t-tau. In parallel, brain ... -
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
Open AccessImage 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, ...
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