Recent advances in crop disease detection using UAV and deep learning techniques
Because of the recent advances in drones or Unmanned Aerial Vehicle (UAV) platforms,
sensors and software, UAVs have gained popularity among precision agriculture …
sensors and software, UAVs have gained popularity among precision agriculture …
A review on UAV-based applications for plant disease detection and monitoring
Remote sensing technology is vital for precision agriculture, aiding in early issue detection,
resource management, and environmentally friendly practices. Recent advances in remote …
resource management, and environmentally friendly practices. Recent advances in remote …
RustQNet: Multimodal deep learning for quantitative inversion of wheat stripe rust disease index
Quantitative remote sensing of crop diseases at the field or plot scale is essential for crop
management. Conventional approaches frequently rely solely on single-modal remote …
management. Conventional approaches frequently rely solely on single-modal remote …
Unoccupied aerial systems imagery for phenotyping in cotton, maize, soybean, and wheat breeding
High‐throughput phenotyping (HTP) with unoccupied aerial systems (UAS), consisting of
unoccupied aerial vehicles (UAV; or drones) and sensor (s), is an increasingly promising …
unoccupied aerial vehicles (UAV; or drones) and sensor (s), is an increasingly promising …
Applying convolutional neural networks for detecting wheat stripe rust transmission centers under complex field conditions using RGB-based high spatial resolution …
The use of unmanned aerial vehicle (UAV) provide a timely and low-cost means of
accessing high spatial resolution imagery for crop disease detection. In this study …
accessing high spatial resolution imagery for crop disease detection. In this study …
Deep learning models outperform generalized machine learning models in predicting winter wheat yield based on multispectral data from drones
Z Li, Z Chen, Q Cheng, S Fei, X Zhou - Drones, 2023 - mdpi.com
Timely and accurate monitoring of winter wheat yields is beneficial for the macro-guidance
of agricultural production and for making precise management decisions throughout the …
of agricultural production and for making precise management decisions throughout the …
Using UAV multispectral remote sensing with appropriate spatial resolution and machine learning to monitor wheat scab
W Zhu, Z Feng, S Dai, P Zhang, X Wei - Agriculture, 2022 - mdpi.com
This study took the wheat grown in the experimental area of Jiangsu Academy of Agricultural
Sciences as the research object and used the unmanned aerial vehicle (UAV) to carry the …
Sciences as the research object and used the unmanned aerial vehicle (UAV) to carry the …
Inversion of chlorophyll content under the stress of leaf mite for jujube based on model PSO-ELM method
During the growth season, jujube trees are susceptible to infestation by the leaf mite, which
reduces the fruit quality and productivity. Traditional monitoring techniques for mites are time …
reduces the fruit quality and productivity. Traditional monitoring techniques for mites are time …
A survey on deep learning-based identification of plant and crop diseases from UAV-based aerial images
The agricultural crop productivity can be affected and reduced due to many factors such as
weeds, pests, and diseases. Traditional methods that are based on terrestrial engines …
weeds, pests, and diseases. Traditional methods that are based on terrestrial engines …
Ultra-High-Resolution UAV-Based Detection of Alternaria solani Infections in Potato Fields
Automatic detection of foliar diseases in potato fields, such as early blight caused by
Alternaria solani, could allow farmers to reduce the application of plant protection products …
Alternaria solani, could allow farmers to reduce the application of plant protection products …