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Drone‐based imaging sensors, techniques, and applications in plant phenoty** for crop breeding: A comprehensive review
Over the last decade, the use of unmanned aerial vehicles (UAVs) for plant phenoty** and
field crop monitoring has significantly evolved and expanded. These technologies have …
field crop monitoring has significantly evolved and expanded. These technologies have …
End-to-End Deep Learning Models for Gap Identification in Maize Fields
We propose an approach to jointly count plants and detect gaps in maize fields using end-to-
end deep-learning models. Unlike previous efforts that focused solely on plant detection our …
end deep-learning models. Unlike previous efforts that focused solely on plant detection our …
Swin-Roleaf: A new method for characterizing leaf azimuth angle in large-scale maize plants
Maize is the most productive grain crop in the world in terms of total production and yield.
Leaf azimuth angle, the directional orientation of the maize leaf, is an important …
Leaf azimuth angle, the directional orientation of the maize leaf, is an important …
Recognition of Maize Tassels Based on Improved YOLOv8 and Unmanned Aerial Vehicles RGB Images
The tasseling stage of maize, as a critical period of maize cultivation, is essential for
predicting maize yield and understanding the normal condition of maize growth. However …
predicting maize yield and understanding the normal condition of maize growth. However …
Object Detection in High-Resolution UAV Aerial Remote Sensing Images of Blueberry Canopy Fruits
Y Zhao, L Yang, X Xu - Agriculture, 2024 - search.proquest.com
Blueberries, as one of the more economically rewarding fruits in the fruit industry, play a
significant role in fruit detection during their growing season, which is crucial for orchard …
significant role in fruit detection during their growing season, which is crucial for orchard …
A rapid and precise algorithm for maize leaf disease detection based on YOLO MSM
Y Meng, J Zhan, K Li, F Yan, L Zhang - Scientific Reports, 2025 - nature.com
Using real-time and precise detection methods for maize leaf disease can significantly
reduce economic losses in agriculture. Practical implementation often faces challenges such …
reduce economic losses in agriculture. Practical implementation often faces challenges such …
Comparison of YOLO-based sorghum spike identification detection models and monitoring at the flowering stage
S Zhang, Y Yang, L Tu, T Fu, S Chen, F Cen, S Yang… - Plant Methods, 2025 - Springer
Monitoring sorghum during the flowering stage is essential for effective fertilization
management and improving yield quality, with spike identification serving as the core …
management and improving yield quality, with spike identification serving as the core …
YOLOv8s-Longan: a lightweight detection method for the longan fruit-picking UAV
J Li, K Wu, M Zhang, H Chen, H Lin, Y Mai… - Frontiers in Plant …, 2025 - frontiersin.org
Introduction Due to the limited computing power and fast flight speed of the picking of
unmanned aerial vehicles (UAVs), it is important to design a quick and accurate detecting …
unmanned aerial vehicles (UAVs), it is important to design a quick and accurate detecting …
[HTML][HTML] A Lightweight Model for Weed Detection Based on the Improved YOLOv8s Network in Maize Fields
To address the issue of the computational intensity and deployment difficulties associated
with weed detection models, a lightweight target detection model for weeds based on …
with weed detection models, a lightweight target detection model for weeds based on …
[HTML][HTML] Monitoring of Broccoli Flower Head Development in Fields Using Drone Imagery and Deep Learning Methods
C Zhang, X Sun, S Xuan, J Zhang, D Zhang, X Yuan… - Agronomy, 2024 - mdpi.com
For different broccoli materials, it used to be necessary to manually plant in a large area for
the investigation of flower ball information, and this method is susceptible to subjective …
the investigation of flower ball information, and this method is susceptible to subjective …