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Article
Leaf area index estimations by deep learning models using RGB images and data fusion in maize
(Springer, 2022-08-05)
The leaf area index (LAI) is a biophysical crop parameter of great interest for agronomists and plant breeders. Direct methods for measuring LAI are normally destructive, while indi rect methods are either costly or ...
PhD Thesis
Caracterización de las royas del trigo en Andalucía y uso de sensores remotos para su detección temprana
(2024-01-17)
Las royas son una enfermedad importante en el cultivo del trigo, generando pérdidas de producción y, por tanto, económicas, en el sector cerealista. Podemos distinguir principalmente tres especies que causan tres ...
Article
Intelligent Fruit Yield Estimation for Orchards Using Deep Learning Based Semantic Segmentation Techniques—A Review
(Frontiers Media S.A., 2021-06)
Smart farming employs intelligent systems for every domain of agriculture to obtain sustainable economic growth with the available resources using advanced technologies. Deep Learning (DL) is a sophisticated artificial ...
PhD Thesis
Development and assessment of AI models based on deep learning algorithms to determine agronomic traits in fruit tree orchards and field crops
(2022-11-23)
It’s been claimed by the scientific community that we will need fifty percent more food by 2050 for a world population of close to 10 billion, resulting in a global crisis which raises the question of whether the global ...
Article
A Mixed Data-Based Deep Neural Network to Estimate Leaf Area Index in Wheat Breeding Trials
(MDPI, 2020)
Remote and non-destructive estimation of leaf area index (LAI) has been a challenge in the last few decades as the direct and indirect methods available are laborious and time-consuming. The recent emergence of high-throughput ...
Article
Deep learning techniques for estimation of the yield and size of citrus fruits using a UAV
(Elsevier, 2021-02-21)
Accurate and early estimation of citrus yields is important for both producers and agricultural cooperatives to be competitive and make informed decisions when selling their products. Yield estimation is key for ...
Article
Article
Tackling unbalanced datasets for yellow and brown rust detection in wheat
(Frontiers, 2024-05)
This study evaluates the efficacy of hyperspectral data for detecting yellow and brown rust in wheat, employing machine learning models and the SMOTE (Synthetic Minority Oversampling Technique) augmentation technique to ...