Detection Method for Rice Seedling Planting Conditions Based on Image Processing and an Improved YOLOv8n Model
Bo Zhao,
Qifan Zhang,
Yangchun Liu
et al.
Abstract:In response to the need for precision and intelligence in the assessment of transplanting machine operation quality, this study addresses challenges such as low accuracy and efficiency associated with manual observation and random field sampling for the evaluation of rice seedling planting conditions. Therefore, in order to build a seedling insertion condition detection system, this study proposes an approach based on the combination of image processing and deep learning. The image processing stage is primaril… Show more
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