Using deep learning for pruning region detection and plant organ segmentation in dormant spur-pruned grapevines.

ABSTRACT: Even though mechanization has dramatically decreased labor requirements, vineyard management costs are still affected by selective operations such as winter pruning. Robotic solutions are becoming more common in agriculture, however, few studies have focused on grapevines. This work aims at fine-tuning and testing two different deep neural networks for: (i) detecting pruning regions (PRs), and (ii) performing organ segmentation of spur-pruned dormant grapevines. The Faster R-CNN network was fine-tuned using 1215 RGB images collected in different vineyards and annotated through bounding boxes. The network was tested on 232 RGB images, PRs were categorized by wood type (W), orientation (Or) and visibility (V), and performance metrics were calculated. PR detection was dramatically affected by

SUBMITTER: Guadagna P 

PROVIDER: S-EPMC10032262 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature