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- W4312668478 abstract "Fertilizer is the food of grain, which has a decisive impact on grain yield. The granulation particle size of fertilizers is one of the important factors affecting product quality. Today, fertilizer production plants still observe the granulation particle size manually. This method is timeconsuming, labor-intensive, and unstable. For this reason, this study uses computer vision technology and high-speed cameras to quickly capture fertilizer granulation particles, uses a control system to control industrial cameras to capture particle size, and then train and optimize the neural network model. Achieve the monitoring of fertilizer granulation production quality, adjust the production factors in real time, and improve the production quality. Finally, it can replace manual work and accomplish unmanned and intelligent granulation detection." @default.
- W4312668478 created "2023-01-05" @default.
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- W4312668478 date "2022-10-20" @default.
- W4312668478 modified "2023-09-27" @default.
- W4312668478 title "Research on quality monitoring technology of fertilizer granulation based on deep learning" @default.
- W4312668478 doi "https://doi.org/10.1117/12.2656485" @default.
- W4312668478 hasPublicationYear "2022" @default.
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