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Novel Applications of Optical Sensors and Machine Learning in Agricultural Monitoring

Agricultural production management is facing a new era of intelligence and automation. With developments in sensor technologies, the temporal, spectral, and spatial resolution from ground/air/space platforms have been notably improved. Optical sensors play an essential role in agriculture production...

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Guardado en:
Formato: Online
Lenguaje:inglés
Publicado: MDPI - Multidisciplinary Digital Publishing Institute 2024
Materias:
soil moisture content
spectral processing technology
hyperspectral
principal component analysis
feature parameters extraction
yield estimation
rice
unmanned aerial vehicle (UAV)
tasseled cap transformation
precision agriculture
weed identification
YOLOv4-Tiny
attention mechanism
multiscale detection
angle normalization
vegetation canopy reflectance
geostationary satellite
path length correction
Minnaert model
GOCI
winter wheat
LSTM
LAI
deep learning
land use
land cover
classification
random forest
Sentinel data
SRTM
feature selection
accuracy
validation
unmanned aerial vehicle
soybean
convolutional neural network
multispectral imagery
fusarium head blight
texture indices
machine learning
cropland
multi-seasonal
fractal feature
feature extraction
accuracy evaluation
black soil
UAV
chlorophyll
fractional vegetation cover
maturity monitoring
anomaly detection
smart agriculture
detection of apple leaf diseases
YOLOv5
transformer
CBAM
crop type classification
multi-temporal
remote sensing
dairy cows
body condition score
3D TOF sensor
non-contact evaluation
recognize area of interest
sugarcane clones
canopy cover
light interception
biomass
cane yield
peanut southern blight
reflection spectrum
spectral index
continuous wavelet transform
VGNet
corn diseases
leaf detection
lightweight
transfer learning
agriculture
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Acceso en línea:ONIX_20240108_9783036597980_103
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ONIX_20240108_9783036597980_103

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