Recognition of Ginger Seed Growth Stages Using a Two-Stage Deep Learning Approach
Yin-Syuen Tong,
Tou-Hong Lee,
Kin-Sam Yen
Abstract:Monitoring the growth of ginger seed relies on human experts due to the lack of salient features for effective recognition. In this study, a region-based convolutional neural network (R-CNN) hybrid detector-classifier model is developed to address the natural variations in ginger sprouts, enabling automatic recognition into three growth stages. Out of 1,746 images containing 2,277 sprout instances, the model predictions revealed significant confusion between growth stages, aligning with the human perception in… Show more
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