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Structural Complexity and Informational Transfer in Spatial Log-Gaussian Cox Processes
(MDPI, 2021-08-31)
The doubly stochastic mechanism generating the realizations of spatial log-Gaussian
Cox processes is empirically assessed in terms of generalized entropy, divergence and complexity
measures. The aim is to characterize ...
Masked Auto-Encoding Spectral-Spatial Transformer for Hyperspectral Image Classification
(IEEE, 2022-10-28)
Deep learning has certainly become the dominant trend in hyperspectral (HS) remote sensing (RS) image classification owing to its excellent capabilities to extract highly discriminating spectral–spatial features. In this ...
First Dirichlet Eigenvalue and Exit Time Moment Spectra Comparisons
(Springer, 2023)
Egocentric video summarisation via purpose-orientedframe scoring and selection
(ElsevierPergamon, 2021-11-02)
Existing video summarisation techniques are quite generic in nature, since they generally overlook the important aspect of what actual purpose the summary will be serving. In sharp contrast with this mainstream work, it ...
Transfer Deep Learning for Remote Sensing Datasets: A Comparison Study
(IEEE, 2022-07-17)
Remote sensing is also benefiting from the quick development of deep learning algorithms for image analysis and classification tasks. In this paper, we evaluate the classification performance of a well-known Convolutional ...
Modulating the Gameplay Challenge Through Simple Visual Computing Elements: A Cube Puzzle Case Study
(UNIR - Universidad Internacional de La Rioja, 2022-05-02)
Positive player’s experiences greatly rely on a balanced gameplay where the game difficulty is related to player’s
skill. Towards this goal, the gameplay can be modulated to make it easier or harder. In this work, a ...
A set of deep learning algorithms for air quality prediction applications
(Elsevier, 2023)
This paper presents a set of machine learning algorithms, including grid-based (Bidirectional Convolutional Long Short-Term Memory) and graph-based (Attention Temporal Graph Convolutional Network) algorithms to predict air ...
Graph Neural Network for Air Quality Prediction: A Case Study in Madrid
(IEEE, 2023)
Air quality monitoring, modelling and forecasting are considered pressing and challenging
topics for citizens and decision-makers, including the government. The tools used to achieve the above goals
vary depending on the ...
Attentional Dense Convolutional Neural Network for Water Body Extraction From Sentinel-2 Images
(IEEE, 2022-08-15)
Monitoring water bodies from remote sensing data is
certainly an essential task to supervise the actual conditions of the
available water resources for environment conservation, sustainable development, and many other ...
Far-field perfect imaging with time-modulated gratings
(American Physical Society, 2022-06-22)
We study the capabilities of time-modulated diffraction gratings as imaging devices. It is shown that a time-dependent but transversally homogeneous slab can be used to make a perfect image of an object in the far-field, ...