Machine learning in agriculture: A comprehensive updated review
The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …
artificial intelligent systems for the sake of making value from the ever-increasing data …
A survey on the applications of convolutional neural networks for synthetic aperture radar: Recent advances
In recent years, convolutional neural networks (CNNs) have drawn considerable attention
for the analysis of synthetic aperture radar (SAR) data. In this study, major subareas of SAR …
for the analysis of synthetic aperture radar (SAR) data. In this study, major subareas of SAR …
SSTNet: Spatial, spectral, and texture aware attention network using hyperspectral image for corn variety identification
Currently, most existing methods using hyperspectral images to assist seed identification
only consider the spectral information but ignore the spatial information resulting in …
only consider the spectral information but ignore the spatial information resulting in …
Review of synthetic aperture radar with deep learning in agricultural applications
Abstract Synthetic Aperture Radar (SAR) observations, valued for their consistent acquisition
schedule and not being affected by cloud cover and variations between day and night, have …
schedule and not being affected by cloud cover and variations between day and night, have …
Synergetic classification of coastal wetlands over the Yellow River Delta with GF-3 full-polarization SAR and Zhuhai-1 OHS hyperspectral remote sensing
The spatial distribution of coastal wetlands affects their ecological functions. Wetland
classification is a challenging task for remote sensing research due to the similarity of …
classification is a challenging task for remote sensing research due to the similarity of …
Identification of crop type based on C-AENN using time series Sentinel-1A SAR data
Crop type identification is the initial stage and an important part of the agricultural monitoring
system. It is well known that synthetic aperture radar (SAR) Sentinel-1A imagery provides a …
system. It is well known that synthetic aperture radar (SAR) Sentinel-1A imagery provides a …
Machine learning in volcanology: a review
A volcano is a complex system, and the characterization of its state at any given time is not
an easy task. Monitoring data can be used to estimate the probability of an unrest and/or an …
an easy task. Monitoring data can be used to estimate the probability of an unrest and/or an …
Crop classification based on multi-temporal PolSAR images with a single tensor network
WT Zhang, L Liu, Y Bai, YB Li, J Guo - Pattern Recognition, 2023 - Elsevier
Accurate and reliable discrimination of crop categories is a significant data source for
agricultural monitoring and food security evaluation research. The convolutional neural …
agricultural monitoring and food security evaluation research. The convolutional neural …
Deep learning method based on spectral characteristic rein-forcement for the extraction of winter wheat planting area in complex agricultural landscapes
H Sun, B Wang, Y Wu, H Yang - Remote Sensing, 2023 - mdpi.com
Winter wheat is one of the most important food crops in the world. Remote sensing
technology can be used to obtain the spatial distribution and planting area of winter wheat in …
technology can be used to obtain the spatial distribution and planting area of winter wheat in …
Soil moisture retrieval in farmland areas with sentinel multi-source data based on regression convolutional neural networks
J Liu, Y Xu, H Li, J Guo - Sensors, 2021 - mdpi.com
As an important component of the earth ecosystem, soil moisture monitoring is of great
significance in the fields of crop growth monitoring, crop yield estimation, variable irrigation …
significance in the fields of crop growth monitoring, crop yield estimation, variable irrigation …