Results 1 to 10 of about 108,472 (220)

Preclinical PET imaging in epileptogenesis: towards identification of biomarkers and therapeutic targets. [PDF]

EJNMMI Res
Background Epilepsy is a neurological disorder that affects a significant portion of the global population. However, its complexity and the lack of biomarkers hinder the study of its etiology, resulting in a lack of effective treatments to slow down or ...
Hernández-Martín N, Pozo-Cabanell I, Fernández de la Rosa R, García-García L, Gómez-Oliver F, Pozo MÁ, Brackhan M, Bascuñana P.   +7 more
europepmc   +2 more sources

Generative Learning for Postprocessing Semantic Segmentation Predictions: A Lightweight Conditional Generative Adversarial Network Based on Pix2pix to Improve the Extraction of Road Surface Areas

Land, 2021
Remote sensing experts have been actively using deep neural networks to solve extraction tasks in high-resolution aerial imagery by means of supervised semantic segmentation operations.
Calimanut-Ionut Cira, Miguel-Ángel Manso-Callejo, Ramón Alcarria, Teresa Fernández Pareja, Borja Bordel Sánchez, Francisco Serradilla   +5 more
doaj   +1 more source

AUTOMATIC SEGMENTATION OF POINT CLOUDS IN THE ARCHITECTURE ENVIRONMENT [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021
Correct and reliable identification and classification of different structures and infrastructures that make up a city (e.g. residential buildings, school buildings, hospitals, power stations, routes of communication, etc.) are of great importance for ...
R. Romero-Jarén, J. J. Arranz, L. Navas-Sánchez, E. Erduran, S. Martínez-Cuevas, B. Benito   +5 more
doaj   +1 more source

Improving Road Surface Area Extraction via Semantic Segmentation with Conditional Generative Learning for Deep Inpainting Operations

ISPRS International Journal of Geo-Information, 2022
The road surface area extraction task is generally carried out via semantic segmentation over remotely-sensed imagery. However, this supervised learning task is often costly as it requires remote sensing images labelled at the pixel level, and the ...
Calimanut-Ionut Cira, Martin Kada, Miguel-Ángel Manso-Callejo, Ramón Alcarria, Borja Bordel Sanchez   +4 more
doaj   +1 more source

Entropía en la ciudad de Zaragoza. Cartografía para analizar la diversidad social y la segregación residencial intraurbana.

Geographicalia, 2023
La medición de la diversidad social y la segregación residencial ha suscitado un notable interés en círculos académicos, técnicos y particularmente en el contexto de la planificación urbana. Sin embargo, la fiabilidad de los instrumentos cartográficos se ha visto condicionada por los métodos y técnicas de análisis geodemográfico y por la disponibilidad
Postigo Vidal, Raúl, Valdivielso Pardos, Sergio, Pueyo Campos, Ãngel   +2 more
openaire   +3 more sources

A Single High Dose of Flufenamic Acid in Rats does not Reduce the Damage Associated with the Rat Lithium-Pilocarpine Model of Status Epilepticus but Leads to Deleterious Outcomes

Journal of Integrative Neuroscience, 2023
Background: Epilepsy is one of the most common neurologic diseases, and around 30% of all epilepsies, particularly the temporal lobe epilepsy (TLE), are highly refractory to current pharmacological treatments. Abnormal synchronic neuronal activity, brain
Nira Hernández-Martín, Francisca Gomez, Ágata Silván, Rubén Fernández de la Rosa, Mercedes Delgado, Pablo Bascuñana, Miguel Ángel Pozo, Luis García-García   +7 more
doaj   +1 more source

The role of GIS in urban seismic risk studies: application to the city of Almería (southern Spain) [PDF]

Natural Hazards and Earth System Sciences, 2013
This work describes the structure and characteristics of the geographic information system (GIS) developed for the urban seismic risk study of the city of Almería (southern Spain), identifying the stages in which the use of this tool proved to be very ...
A. Rivas-Medina, J. M. Gaspar-Escribano, B. Benito, M. A. Bernabé   +3 more
doaj   +1 more source

State-Level Mapping of the Road Transport Network from Aerial Orthophotography: An End-to-End Road Extraction Solution Based on Deep Learning Models Trained for Recognition, Semantic Segmentation and Post-Processing with Conditional Generative Learning

Remote Sensing, 2023
Most existing road extraction approaches apply learning models based on semantic segmentation networks and consider reduced study areas, featuring favorable scenarios. In this work, an end-to-end processing strategy to extract the road surface areas from
Calimanut-Ionut Cira, Miguel-Ángel Manso-Callejo, Ramón Alcarria, Borja Bordel Sánchez, Javier González Matesanz   +4 more
doaj   +1 more source

Design and Research of a Multipurpose Cadastre for the Development of Smart Communities in Municipalities of Chile

Environmental Sciences Proceedings, 2023
In many governments, a digital transformation is gradually taking place in their municipal governance, not without many difficulties due to the lack of resources and qualified professionals.
Daniel Flores-Rozas, Miguel-Ángel Manso-Callejo, Sandra Martínez-Cuevas   +2 more
doaj   +1 more source

First Dataset of Wind Turbine Data Created at National Level With Deep Learning Techniques From Aerial Orthophotographs With a Spatial Resolution of 0.5 M/Pixel

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Deep learning applied to feature extraction and mapping from high-resolution images is demonstrating the potential of this branch of data-intensive Artificial Intelligence to improve terrain mapping processes. The documented experiences have been applied
Miguel-Angel Manso-Callejo, Calimanut-Ionut Cira, Ramon Pablo Alcarria Garrido, Francisco Javier Gonzalez Matesanz   +3 more
doaj   +1 more source