Resources for image-based high-throughput phenotyping in crops and data sharing challenges
High-throughput phenotyping (HTP) platforms are capable of monitoring the phenotypic
variation of plants through multiple types of sensors, such as red green and blue (RGB) …
variation of plants through multiple types of sensors, such as red green and blue (RGB) …
Comparison of deep learning methods for detecting and counting sorghum heads in UAV imagery
H Li, P Wang, C Huang - Remote Sensing, 2022 - mdpi.com
With the rapid development of remote sensing with small, lightweight unmanned aerial
vehicles (UAV), efficient and accurate crop spike counting, and yield estimation methods …
vehicles (UAV), efficient and accurate crop spike counting, and yield estimation methods …
A deep learning semantic segmentation-based approach for field-level sorghum panicle counting
Small unmanned aerial systems (UAS) have emerged as high-throughput platforms for the
collection of high-resolution image data over large crop fields to support precision …
collection of high-resolution image data over large crop fields to support precision …
Towards improved accuracy of UAV-based wheat ears counting: A transfer learning method of the ground-based fully convolutional network
J Ma, Y Li, H Liu, Y Wu, L Zhang - Expert Systems with Applications, 2022 - Elsevier
In order to achieve accurate UAV-based wheat ear counting, a transfer learning method of
the ground-based fully convolutional network, ie, EarDensityNet, was proposed in this study …
the ground-based fully convolutional network, ie, EarDensityNet, was proposed in this study …
Color calibration of proximal sensing RGB images of oilseed rape canopy via deep learning combined with K-means algorithm
Plant color is a key feature for estimating parameters of the plant grown under different
conditions using remote sensing images. In this case, the variation in plant color should be …
conditions using remote sensing images. In this case, the variation in plant color should be …
Quantitative estimation of wheat phenotyping traits using ground and aerial imagery
This study evaluates an aerial and ground imaging platform for assessment of canopy
development in a wheat field. The dependence of two canopy traits, height and vigour, on …
development in a wheat field. The dependence of two canopy traits, height and vigour, on …
On‐the‐go assessment of vineyard canopy porosity, bunch and leaf exposure by image analysis
Abstract Background and Aims Canopy assessment of the fruiting zone can lead to more
informed vineyard management decisions. A non‐destructive, image‐based system capable …
informed vineyard management decisions. A non‐destructive, image‐based system capable …
Development of a mobile application for identification of grapevine (Vitis vinifera L.) cultivars via deep learning
Y Liu, J Su, L Shen, N Lu, Y Fang… - … of agricultural and …, 2021 - repository.essex.ac.uk
Traditional vine variety identification methods usually rely on the sampling of vine leaves
followed by physical, physiological, biochemical and molecular measurement, which are …
followed by physical, physiological, biochemical and molecular measurement, which are …
Color Consistency of UAV Imagery using Multi-Channel CNN-based Image-to-Image Regression and Residual Learning
Remote sensing images often suffer from color distortion, which can pose significant
challenges for accurate data interpretation. To overcome this issue, this study developed a …
challenges for accurate data interpretation. To overcome this issue, this study developed a …
Machine learning methods for automatic segmentation of images of field-and glasshouse-based plants for high-throughput phenotyping
Image segmentation is a fundamental but critical step for achieving automated high-
throughput phenotyping. While conventional segmentation methods perform well in …
throughput phenotyping. While conventional segmentation methods perform well in …