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Application of Vision Technology and Artificial Intelligence in Smart Farming

Artificial intelligence (AI) has been gaining traction in smart agriculture. Machine learning (ML) can be used for environmental and production performance data analysis and prediction, and computer vision (CV) can monitor abnormal phenotypes in plants and animals. They have massive potential to enh...

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Gespeichert in:
Format: Online
Sprache:Englisch
Veröffentlicht: MDPI - Multidisciplinary Digital Publishing Institute 2024
Schlagworte:
grain pest classification
visual attention mechanism
discrete wavelet transform
deep learning
computer vision
laying hens
feeding behavior
Faster R-CNN
model visualization
P. orientalis
recurrent neural network
inverse distance weighting
accumulated air temperature
dairy cow
individual identification
body pattern image
binarization
cascaded classification
Kinect
crop phenotypic
point cloud processing
three-dimensional reconstruction
singular value decomposition
mobile edge computing
convolutional neural network
deep reinforcement learning
wheat growth stages detection
dynamic migration algorithm
rice seed
variety classification
multimodal fusion
machine vision
point cloud
YOLOv5
deformable convolution
attention mechanism
visual detection system
Zanthoxylum-harvesting robot
soil moisture
prediction
XGBoost algorithm
SHAP
dual attention mechanism
multi-scale feature extraction
RFCA ResNet
classification
3D reconstruction
the whole growth period
soybean
point cloud segmentation
dataset
bee mite
image processing
keypoint detection
image matching
cow udder classification
udder features
instance segmentation
CNN-LSTM
udder conformation
precision farming
smart farming
agricultural technology
Internet of Things (IoT)
big data analytics
machine learning
artificial intelligence (AI)
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
Online-Zugang:ONIX_20240514_9783039285976_91
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ONIX_20240514_9783039285976_91

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