Applying Remote Sensing Methods to Estimate Alterations in Land Cover Change and Degradation in the Desert Regions of the Southeast Iberian Peninsula

Autor: Emilio Ramírez-Juidias, Antonio Madueño-Luna, José Miguel Madueño-Luna, Miguel Calixto López-Gordillo, Jorge Luis Leiva-Piedra

Publikováno v: Remote Sensing, Vol 15, Iss 16, p 3984 (2023)

Numerous drylands worldwide have experienced degradation of both soil and vegetation in proximity to watering areas. Degradation can be observed in satellite imagery as fading radial brightness belts extending away from the water sources. The main ob

Externí odkaz: https://doaj.org/article/6adbec1eb0184dd891a18573a3620173

Classification of Monofloral Honeys by Measuring Electrical Impedance Based on Neural Networks

Autor: Eduardo González María, Antonio Madueño-Luna, Antonio Ruiz-Canales, José Miguel Madueño Luna

Publikováno v: Agronomy, Vol 12, Iss 8, p 1929 (2022)

The study of electrical impedance applied to food has become a method with great potential for use in the food industry, which allows the monitoring and control of quality processes in a safe and non-invasive way. Recent research has shown that this

Externí odkaz: https://doaj.org/article/49a094d363e44154a7f8e2e944a42ddc

Assessing the Best Gap-Filling Technique for River Stage Data Suitable for Low Capacity Processors and Real-Time Application Using IoT

Autor: Miriam López Lineros, Antonio Madueño Luna, Javier Estévez Gualda, Juan Vicente Giráldez Cervera, José Miguel Madueño Luna

Publikováno v: Sensors, Vol 20, Iss 6354, p 6354 (2020)
Sensors (Basel, Switzerland)
Sensors
Volume 20
Issue 21
idUS: Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
idUS. Depósito de Investigación de la Universidad de Sevilla
instname

Hydrometeorological data sets are usually incomplete due to different reasons (malfunctioning sensors, collected data storage problems, etc.). Missing data do not only affect the resulting decision-making process, but also the choice of a particular

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33bcd44ecc167630075ef653f08d5993
https://www.mdpi.com/1424-8220/20/21/6354

Análisis en tiempo real del funcionamiento de la cadena de alimentación de las máquinas deshuesadoras de aceitunas mediante diagnosis por visión artificial y redes neuronales

Autor: José Miguel Molina Martínez, Meritxell Justicia Segovia, Antonio Ruiz Canales, Montserrat Baena Sánchez, Antonio Madueño Luna, Manuel de Jódar Lázaro, Alberto Lucas Pascual, José Miguel Madueño Luna

Publikováno v: Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname
Repositorio Digital de la Universidad Politécnica de Cartagena
Fundación Universitaria San Pablo CEU (FUSPCEU)

Las maquinas deshuesadoras de aceitunas se caracterizan porque su funcionamiento optimo esta vinculado a un buen ajuste: Seleccion de un plato de alimentacion adecuado a la variedad de aceituna y su calibre, de las caracteristicas geometricas de la c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a08d301f65426bdae15b7f24f23c1d7
https://doi.org/10.26754/c_agroing.2019.com.3423

Deep learning in olive pitting machines by computer vision

Autor: Meritxel Justicia Segovia, José Miguel Madueño Luna, Montserrat Baena Sánchez, Antonio Madueño Luna, José Miguel Molina Martínez, Alberto Lucas Pascual, Manuel de Jódar Lázaro, Antonio Ruiz Canales

Publikováno v: Computers and Electronics in Agriculture. 171:105304

Olive pitting machines are characterized by the fact that their optimal functioning is based on an appropriate adjustment: selection of a feed plate adapted to the olive variety and its caliber, geometrical characteristics of the feed chain, etc. The

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5edfd457a68f1ccd06e4087768880c8c
https://doi.org/10.1016/j.compag.2020.105304