A three-dimensional conceptual model for estimating the above-ground biomass of winter wheat using digital and multispectral unmanned aerial vehicle images at …
Y Zhu, J Liu, X Tao, X Su, W Li, H Zha, W Wu, X Li - Remote Sensing, 2023 - mdpi.com
The timely and accurate estimation of above-ground biomass (AGB) is crucial for indicating
crop growth status, assisting management decisions, and predicting grain yield. Unmanned …
crop growth status, assisting management decisions, and predicting grain yield. Unmanned …
Yolo-fr: A yolov5 infrared small target detection algorithm based on feature reassembly sampling method
X Mou, S Lei, X Zhou - Sensors, 2023 - mdpi.com
The loss of infrared dim-small target features in the network sampling process is a major
factor affecting its detection accuracy. In order to reduce this loss, this paper proposes YOLO …
factor affecting its detection accuracy. In order to reduce this loss, this paper proposes YOLO …
A Review of Individual Tree Crown Detection and Delineation From Optical Remote Sensing Images: Current progress and future
Powered by advances of optical remote sensing sensors, the production of very high spatial
resolution multispectral images provides great potential for achieving cost-efficient and high …
resolution multispectral images provides great potential for achieving cost-efficient and high …
Impact of deep convolutional neural network structure on photovoltaic array extraction from high spatial resolution remote sensing images
Accurate information on the location, shape, and size of photovoltaic (PV) arrays is essential
for optimal power system planning and energy system development. In this study, we …
for optimal power system planning and energy system development. In this study, we …
Open-set domain adaptation for scene classification using multi-adversarial learning
Abstract Domain adaptation methods are able to transfer knowledge across different
domains, tackling multi-sensor, multi-temporal or cross-regional remote sensing scenarios …
domains, tackling multi-sensor, multi-temporal or cross-regional remote sensing scenarios …
Early symptom detection of basal stem rot disease in oil palm trees using a deep learning approach on UAV images
OW Kent, TW Chun, TL Choo, LW Kin - Computers and Electronics in …, 2023 - Elsevier
The oil palm tree (Elaeis guineensis Jacq.) is a vital and economically important plant, as the
oil from its fruit is a primary export for many Southeast Asian countries. Hence the health of …
oil from its fruit is a primary export for many Southeast Asian countries. Hence the health of …
Red palm weevil detection in date palm using temporal uav imagery
Red palm weevil (RPW) is widely considered a key pest of palms, creating extensive
damages to the date palm trunk that inevitably leads to palm death if no pest eradication is …
damages to the date palm trunk that inevitably leads to palm death if no pest eradication is …
Sub-national scale map** of individual olive trees integrating Earth observation and deep learning
The olive tree holds great cultural, environmental, and economic significance in the
Mediterranean region. In particular, Morocco has been making dedicated investments over …
Mediterranean region. In particular, Morocco has been making dedicated investments over …
A novel bottleneck residual and self-attention fusion-assisted architecture for land use recognition in remote sensing images
The massive yearly population growth is causing hazards to spread swiftly around the world
and have a detrimental impact on both human life and the world economy. By ensuring early …
and have a detrimental impact on both human life and the world economy. By ensuring early …
A Spatial Distribution Extraction Method for Winter Wheat Based on Improved U-Net
J Liu, H Wang, Y Zhang, X Zhao, T Qu, H Tian, Y Lu… - Remote Sensing, 2023 - mdpi.com
This paper focuses on the problems of omission, misclassification, and inter-adhesion due to
overly dense distribution, intraclass diversity, and interclass variability when extracting …
overly dense distribution, intraclass diversity, and interclass variability when extracting …