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. BiomSHARP: Biomass Super-Resolution for High Accuracy Prediction. IEEE Transactions on Geoscience and Remote Sensing. 2025;63:1-18.
. Comparative Analysis of Tree Segmentation Techniques on High- and Low-Density LiDAR data. In International Conference on Advanced Remote Sensing (ICARS 2025). Basel, Switzerland: MDPI; 2025.
. Comparison of Conventional Machine Learning and Convolutional Deep Learning models for Seagrass Mapping using Satellite Imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2025;:1-19.
. Análisis multiresolución espacial del estado de conservación de un bosque de laurisilvas con sensores pasivos y activos de teledetección. In XX Congreso de la Asociación Española de Teledetección. Cádiz, España: Universidad de Cádiz; 2024.
. Generación de mapas de comunidades y hábitats bentónicos mediante el modelo Deep Learning U-Net utilizando imágenes satelitales multiespectrales de muy alta resolución. In XX Congreso de la Asociación Española de Teledetección. Cádiz, España: Universidad de Cádiz; 2024.
. SEG-ESRGAN: A multi-task network for super-resolution and semantic segmentation of remote sensing images. Remote Sensing. 2022;14(22).
. Super-resolution and semantic segmentation of remote sensing images using deep learning techniques. . Signal Theory and Communications Department. 2022.
. A Dual Network for Super-Resolution and Semantic Segmentation of Sentinel-2 imagery. Remote Sensing. 2021;13(22):4547.
. Single-image super-resolution of Sentinel-2 low resolution bands with residual dense convolutional neural networks. Remote Sensing. 2021;13(24):5007.
. Super-Resolution of Sentinel-2 Imagery Using Generative Adversarial Networks. Remote Sensing. 2020;12(15).
. Comparative study of upsampling methods for super-resolution in remote sensing. In International Conference on Machine Vision. 2019.
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