Deep learning techniques to classify agricultural crops through UAV imagery: A review

A Bouguettaya, H Zarzour, A Kechida… - Neural computing and …, 2022 - Springer
During the last few years, Unmanned Aerial Vehicles (UAVs) technologies are widely used
to improve agriculture productivity while reducing drudgery, inspection time, and crop …

A systematic literature review on crop yield prediction with deep learning and remote sensing

P Muruganantham, S Wibowo, S Grandhi, NH Samrat… - Remote Sensing, 2022 - mdpi.com
Deep learning has emerged as a potential tool for crop yield prediction, allowing the model
to automatically extract features and learn from the datasets. Meanwhile, smart farming …

Crop yield estimation based on assimilation of crop models and remote sensing data: A systematic evaluation

L Luo, S Sun, J Xue, Z Gao, J Zhao, Y Yin, F Gao… - Agricultural …, 2023 - Elsevier
CONTEXT With the warming trend and the increasing frequency of extreme weather events,
accurate crop yield estimation is becoming urgent. Crop yield estimation mainly consists of …

Improving wheat yield prediction integrating proximal sensing and weather data with machine learning

G Ruan, X Li, F Yuan, D Cammarano… - … and Electronics in …, 2022 - Elsevier
Accurate and timely wheat yield prediction is of great importance to global food security.
Early prediction of wheat yield at a field scale is essential for site-specific precision …

[HTML][HTML] Field-level crop yield estimation with PRISMA and Sentinel-2

M Marshall, M Belgiu, M Boschetti, M Pepe… - ISPRS journal of …, 2022 - Elsevier
Satellite image data deliver consistent and frequent information for crop yield estimation
over large areas. Hyperspectral narrowbands are more sensitive spectrally to changes in …

Integrating satellite-derived climatic and vegetation indices to predict smallholder maize yield using deep learning

L Zhang, Z Zhang, Y Luo, J Cao, R **e, S Li - Agricultural and Forest …, 2021 - Elsevier
Timely and accurately estimating smallholder crop yield is essential for optimizing
agronomic management, guiding investment and policy-making to reduce poverty and …