Results 1 to 10 of about 4,977 (68)

Dataset containing orthoimages tagged with road information covering approximately 8650 km2 of the Spanish territory (SROADEX)

Data in Brief, 2022
In this data paper, we propose an open dataset (named SROADEX) containing more than 527,000 image tiles of 256 × 256 pixels stored in the lossless PNG format, tagged at pixel level with road information.
Miguel-Ángel Manso-Callejo, Calimanut-Ionut Cira, Alicia González-Jiménez, José-Javier Querol-Pascual   +3 more
doaj   +1 more source

Assessment of the large-scale extraction of photovoltaic (PV) panels with a workflow based on artificial neural networks and algorithmic postprocessing of vectorization results

International Journal of Applied Earth Observations and Geoinformation, 2023
Having a complete and high-quality geospatial catalogue of existing large-scale photovoltaic (PV) panels is very important nowadays, due to the rapid increase in the use of this type of installations.
Miguel-Ángel Manso-Callejo, Calimanut-Ionut Cira, José-Juan Arranz-Justel, Izar Sinde-González, Tudor Sălăgean   +4 more
doaj   +1 more source

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

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

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

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

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

Diseño para el conocimiento reglado de acceso libre a través de Internet

Arbor: Ciencia, Pensamiento y Cultura, 2011
El impacto de las tecnologías de la información y la comunicación, TIC, ha abierto, un campo de posibilidades casi ilimitadas para comunicar y compartir la información.
M. C. Morillo Balsera, L. Sebastian Lorente, M. L. Casado Fuente   +2 more
doaj   +1 more source