[HTML][HTML] Convolutional neural networks for image-based high-throughput plant phenoty**: a review
Plant phenoty** has been recognized as a bottleneck for improving the efficiency of
breeding programs, understanding plant-environment interactions, and managing …
breeding programs, understanding plant-environment interactions, and managing …
Scaling up high-throughput phenoty** for abiotic stress selection in the field
Key message High-throughput phenoty** (HTP) is in its infancy for deployment in large-
scale breeding programmes. With the ability to measure correlated traits associated with …
scale breeding programmes. With the ability to measure correlated traits associated with …
Semantic segmentation using deep learning with vegetation indices for rice lodging identification in multi-date UAV visible images
A rapid and precise large-scale agricultural disaster survey is a basis for agricultural disaster
relief and insurance but is labor-intensive and time-consuming. This study applies …
relief and insurance but is labor-intensive and time-consuming. This study applies …
Classification of histopathological biopsy images using ensemble of deep learning networks
SH Kassani, PH Kassani, MJ Wesolowski… - ar** by using transfer learning
Crop type map** currently represents an important problem in remote sensing. Accurate
information on the extent and types of crops derived from remote sensing can help …
information on the extent and types of crops derived from remote sensing can help …
Automated machine learning for high-throughput image-based plant phenoty**
JCO Koh, G Spangenberg, S Kant - Remote Sensing, 2021 - mdpi.com
Automated machine learning (AutoML) has been heralded as the next wave in artificial
intelligence with its promise to deliver high-performance end-to-end machine learning …
intelligence with its promise to deliver high-performance end-to-end machine learning …
Wheat lodging detection from UAS imagery using machine learning algorithms
The current mainstream approach of using manual measurements and visual inspections for
crop lodging detection is inefficient, time-consuming, and subjective. An innovative method …
crop lodging detection is inefficient, time-consuming, and subjective. An innovative method …
An explainable XGBoost model improved by SMOTE-ENN technique for maize lodging detection based on multi-source unmanned aerial vehicle images
Remote sensing image is becoming an increasingly popular tool for crop lodging detection
because it conveniently provides features for building machine learning models and …
because it conveniently provides features for building machine learning models and …