A survey on the role of Internet of Things for adopting and promoting Agriculture 4.0
There is a rapid increase in the adoption of emerging technologies like the Internet of Things
(IoT), Unmanned Aerial Vehicles (UAV), Internet of Underground Things (IoUT), Data …
(IoT), Unmanned Aerial Vehicles (UAV), Internet of Underground Things (IoUT), Data …
An overview of global leaf area index (LAI): Methods, products, validation, and applications
H Fang, F Baret, S Plummer… - Reviews of …, 2019 - Wiley Online Library
Leaf area index (LAI) is a critical vegetation structural variable and is essential in the
feedback of vegetation to the climate system. The advancement of the global Earth …
feedback of vegetation to the climate system. The advancement of the global Earth …
Machine learning approaches for crop yield prediction and nitrogen status estimation in precision agriculture: A review
Accurate yield estimation and optimised nitrogen management is essential in agriculture.
Remote sensing (RS) systems are being more widely used in building decision support tools …
Remote sensing (RS) systems are being more widely used in building decision support tools …
A review of remote sensing applications in agriculture for food security: Crop growth and yield, irrigation, and crop losses
The global population is expected to reach 9.8 billion by 2050. There is an exponential
growth of food production to meet the needs of the growing population. However, the limited …
growth of food production to meet the needs of the growing population. However, the limited …
Deep learning for hyperspectral image classification: An overview
Hyperspectral image (HSI) classification has become a hot topic in the field of remote
sensing. In general, the complex characteristics of hyperspectral data make the accurate …
sensing. In general, the complex characteristics of hyperspectral data make the accurate …
Perceiving spectral variation: Unsupervised spectrum motion feature learning for hyperspectral image classification
Y Sun, B Liu, X Yu, A Yu, K Gao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In recent years, deep-learning-based hyperspectral image (HSI) classification methods have
achieved significant development. The superior capability of feature extraction from these …
achieved significant development. The superior capability of feature extraction from these …
Transfer-learning-based approach for leaf chlorophyll content estimation of winter wheat from hyperspectral data
Leaf chlorophyll, as a key factor for carbon circulation in the ecosystem, is significant for the
photosynthetic productivity estimation and crop growth monitoring in agricultural …
photosynthetic productivity estimation and crop growth monitoring in agricultural …
Spectral partitioning residual network with spatial attention mechanism for hyperspectral image classification
Hyperspectral image (HSI) classification is one of the most important tasks in hyperspectral
data analysis. Convolutional neural networks (CNN) have been introduced to HSI …
data analysis. Convolutional neural networks (CNN) have been introduced to HSI …
UAV-based multispectral remote sensing for precision agriculture: A comparison between different cameras
L Deng, Z Mao, X Li, Z Hu, F Duan, Y Yan - ISPRS journal of …, 2018 - Elsevier
Unmanned aerial vehicle (UAV)-based multispectral remote sensing has shown great
potential for precision agriculture. However, there are many problems in data acquisition …
potential for precision agriculture. However, there are many problems in data acquisition …
Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery
Timely and non-destructive assessment of crop yield is an essential part of agricultural
remote sensing (RS). The development of unmanned aerial vehicles (UAVs) has provided a …
remote sensing (RS). The development of unmanned aerial vehicles (UAVs) has provided a …