Neuromorphic applications in medicine
In recent years, there has been a growing demand for miniaturization, low power
consumption, quick treatments, and non-invasive clinical strategies in the healthcare …
consumption, quick treatments, and non-invasive clinical strategies in the healthcare …
Three-dimensional nanoimaging of fuel cell catalyst layers
Catalyst layers in proton exchange membrane fuel cells consist of platinum-group-metal
nanocatalysts supported on carbon aggregates, forming a porous structure through which …
nanocatalysts supported on carbon aggregates, forming a porous structure through which …
Boosting the signal-to-noise of low-field MRI with deep learning image reconstruction
Recent years have seen a resurgence of interest in inexpensive low magnetic field (< 0.3 T)
MRI systems mainly due to advances in magnet, coil and gradient set designs. Most of these …
MRI systems mainly due to advances in magnet, coil and gradient set designs. Most of these …
Learning maximally monotone operators for image recovery
We introduce a new paradigm for solving regularized variational problems. These are
typically formulated to address ill-posed inverse problems encountered in signal and image …
typically formulated to address ill-posed inverse problems encountered in signal and image …
Systematic review on learning-based spectral CT
Spectral computed tomography (CT) has recently emerged as an advanced version of
medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two …
medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two …
A photogrammetry-based workflow for the accurate 3D construction and visualization of museums assets
Nowadays digital replicas of artefacts belonging to the Cultural Heritage (CH) are one of the
most promising innovations for museums exhibitions, since they foster new forms of …
most promising innovations for museums exhibitions, since they foster new forms of …
A trainable spectral-spatial sparse coding model for hyperspectral image restoration
Hyperspectral imaging offers new perspectives for diverse applications, ranging from the
monitoring of the environment using airborne or satellite remote sensing, precision farming …
monitoring of the environment using airborne or satellite remote sensing, precision farming …
Crack segmentation network using additive attention gate—CSN-II
One of the emerging and powerful tools of Artificial Intelligence (AI) in computer vision is
Convolutional Neural Network (CNN) which can outperform traditional algorithms for crack …
Convolutional Neural Network (CNN) which can outperform traditional algorithms for crack …
Deep learning approach for denoising low-SNR correlation plenoptic images
Abstract Correlation Plenoptic Imaging (CPI) is a novel volumetric imaging technique that
uses two sensors and the spatio-temporal correlations of light to detect both the spatial …
uses two sensors and the spatio-temporal correlations of light to detect both the spatial …
[HTML][HTML] Deep learning prediction of motor performance in stroke individuals using neuroimaging data
The degree of motor impairment and profile of recovery after stroke are difficult to predict for
each individual. Measures obtained from clinical assessments, as well as …
each individual. Measures obtained from clinical assessments, as well as …