Recent advances of hyperspectral imaging technology and applications in agriculture
Remote sensing is a useful tool for monitoring spatio-temporal variations of crop
morphological and physiological status and supporting practices in precision farming. In …
morphological and physiological status and supporting practices in precision farming. In …
A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities
Due to limited resources and environmental pollution, monitoring the geological
environment has become essential for many countries' sustainable development. As various …
environment has become essential for many countries' sustainable development. As various …
WHU-Hi: UAV-borne hyperspectral with high spatial resolution (H2) benchmark datasets and classifier for precise crop identification based on deep convolutional …
Unmanned aerial vehicle (UAV)-borne hyperspectral systems can acquire hyperspectral
imagery with a high spatial resolution (which we refer to here as H 2 imagery). As a result of …
imagery with a high spatial resolution (which we refer to here as H 2 imagery). As a result of …
Boost precision agriculture with unmanned aerial vehicle remote sensing and edge intelligence: A survey
J Liu, J Xiang, Y Jin, R Liu, J Yan, L Wang - Remote Sensing, 2021 - mdpi.com
In recent years unmanned aerial vehicles (UAVs) have emerged as a popular and cost-
effective technology to capture high spatial and temporal resolution remote sensing (RS) …
effective technology to capture high spatial and temporal resolution remote sensing (RS) …
Multiscale spatial–spectral transformer network for hyperspectral and multispectral image fusion
Fusing hyperspectral images (HSIs) and multispectral images (MSIs) is an economic and
feasible way to obtain images with both high spectral resolution and spatial resolution. Due …
feasible way to obtain images with both high spectral resolution and spatial resolution. Due …
Support vector machine in precision agriculture: a review
ZH Kok, ARM Shariff, MSM Alfatni… - … and Electronics in …, 2021 - Elsevier
Abstract The Support Vector Machine (SVM) is a Machine Learning (ML) algorithm which
may be used for acquiring solutions towards better crop management. The applications of …
may be used for acquiring solutions towards better crop management. The applications of …
Are unmanned aerial vehicle-based hyperspectral imaging and machine learning advancing crop science?
The past few years have seen increased interest in unmanned aerial vehicle (UAV)-based
hyperspectral imaging (HSI) and machine learning (ML) in agricultural research …
hyperspectral imaging (HSI) and machine learning (ML) in agricultural research …
UAV remote sensing detection of tea leaf blight based on DDMA-YOLO
W Bao, Z Zhu, G Hu, X Zhou, D Zhang… - Computers and Electronics …, 2023 - Elsevier
Tea leaf blight (TLB) is a common disease that affects the yield and quality of tea. Timely and
accurate detection and monitoring of TLB can help support the precise control of the …
accurate detection and monitoring of TLB can help support the precise control of the …
Enhancing assessment of corn growth performance using unmanned aerial vehicles (UAVs) and deep learning
The advancement of unmanned aerial vehicles (UAVs) offers precise and accurate spectral
and spatial information about crops and plays a pivotal role in precision agriculture. This …
and spatial information about crops and plays a pivotal role in precision agriculture. This …
Crop monitoring in smallholder farms using unmanned aerial vehicles to facilitate precision agriculture practices: a scoping review and bibliometric analysis
In this study, we conducted a scoping review and bibliometric analysis to evaluate the state-
of-the-art regarding actual applications of unmanned aerial vehicle (UAV) technologies to …
of-the-art regarding actual applications of unmanned aerial vehicle (UAV) technologies to …