AUTOMATED CLASSIFICATION OF CROP TYPES AND CONDITION IN A MEDITERRANEAN AREA USING A FINE-TUNED CONVOLUTIONAL NEURAL NETWORK

7 citations as recorded by crossref.

1. Assessing the Sentinel-2 Capabilities to Identify Abandoned Crops Using Deep Learning E. Portalés-Julià et al. 10.3390/agronomy11040654
2. Deep learning para la clasificación de usos de suelo agrícola con Sentinel-2 M. Campos-Taberner et al. 10.4995/raet.2020.13337
3. Convolutional Neural Networks for Agricultural Land Use Classification from Sentinel-2 Image Time Series A. Simón Sánchez et al. 10.3390/rs14215373
4. Assessing the capabilities of high-resolution spectral, altimetric, and textural descriptors for mapping the status of citrus parcels S. Morell-Monzó et al. 10.1016/j.compag.2022.107504
5. Imagery Time Series Cloud Removal and Classification Using Long Short Term Memory Neural Networks F. Alonso-Sarria et al. 10.3390/rs16122150
6. Identification of Olives Using In-Field Hyperspectral Imaging with Lightweight Models S. Domínguez-Cid et al. 10.3390/s24051370
7. Advancements in Remote Sensing Imagery Applications for Precision Management in Olive Growing: A Systematic Review P. Marques et al. 10.3390/rs16081324