MAPPING CROP STATUS FROM AN UNMANNED AERIAL VEHICLE FOR PRECISION AGRICULTURE APPLICATIONS

11 citations as recorded by crossref.

1. Application of a Real-Time Field-Programmable Gate Array-Based Image-Processing System for Crop Monitoring in Precision Agriculture S. Antora et al. https://doi.org/10.3390/agriengineering6030191
2. High-Throughput Biomass Estimation in Rice Crops Using UAV Multispectral Imagery C. Devia et al. https://doi.org/10.1007/s10846-019-01001-5
3. Detection of irrigation inhomogeneities in an olive grove using the NDRE vegetation index obtained from UAV images J. Jorge et al. https://doi.org/10.1080/22797254.2019.1572459
4. Estimation of Peanut Leaf Area Index from Unmanned Aerial Vehicle Multispectral Images H. Qi et al. https://doi.org/10.3390/s20236732
5. Enhanced Path Planning by Repositioning the Starting Point G. Gasteratos & I. Karydis https://doi.org/10.3390/app15168786
6. Research on agricultural monitoring and progressive map creation in the context of ground-air coordination X. Li https://doi.org/10.1088/1742-6596/2815/1/012043
7. Toward Modern Pesticide Use Reduction Strategies in Advancing Precision Agriculture: A Bibliometric Review S. Lupica et al. https://doi.org/10.3390/agriengineering7100346
8. Using Deep Learning and Low-Cost RGB and Thermal Cameras to Detect Pedestrians in Aerial Images Captured by Multirotor UAV D. De Oliveira & M. Wehrmeister https://doi.org/10.3390/s18072244
9. Homography vs similarity transformation in aerial mosaicking: which is the best at different altitudes? D. Avola et al. https://doi.org/10.1007/s11042-020-08758-0
10. Artificial intelligence and deep learning based technologies for emerging disease recognition and pest prediction in beans (phaseolus vulgaris l.): A systematic review P. Michael et al. https://doi.org/10.5897/AJAR2022.16226
11. Unmixing-Based Fusion of Hyperspatial and Hyperspectral Airborne Imagery for Early Detection of Vegetation Stress S. Delalieux et al. https://doi.org/10.1109/JSTARS.2014.2330352