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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Bibliografiset tiedot
Aineistotyyppi:	Online
Kieli:	englanti
Julkaistu:	MDPI - Multidisciplinary Digital Publishing Institute 2024
Aiheet:	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
Linkit:	ONIX_20240514_9783039285976_91
Tagit:	Lisää tagi Ei tageja, Lisää ensimmäinen tagi!

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Application of Vision Technology and Artificial Intelligence in Smart Farming

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