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Deep learning-based application for automated leaf counting in medicinal orchid Dendrobium nobile L. using YOLOv5
Abstract Deep learning-based methods have shown promise for automated leaf detection and counting, particularly in rosette species. However, automated leaf counting remains limited for orchids such as Dendrobium nobile, which have a complex non-rosette architecture, alternate phyllotaxy, overlapping leaves, and view-dependent occlusion. This study developed an automated leaf-counting framework for D.
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