Vineyard dataset for automatic pruning based on main parts localization
| Type of publication: | Article |
| Citation: | |
| Publication status: | Published |
| Journal: | Data in Brief, Elsevier |
| Volume: | 59 |
| Year: | 2025 |
| Month: | April |
| URL: | https://www.sciencedirect.com/... |
| DOI: | https://doi.org/10.1016/j.dib.2025.111335 |
| Abstract: | This dataset provides a collection of labeled images related to different parts of the vineyard (trunk, shoot, and pruned shoot), collected in Badajoz, Spain, during 2021 and 2022. The labels were created with VGG Image Annotator (VIA) software. The dataset is particularly suitable for the development of object detection models, providing a solid basis for numerous applications in smart agriculture. Considering the growing importance of precision agriculture, this data provides a valuable starting point for implementing advanced solutions. In addition, the dataset has been used to train Mask R-CNN models for precise localization of plant parts, demonstrating its value for visual processing in agricultural settings. |
| Keywords: | computer vision, object detection, Robotics, Smart Agriculture, Vineyard pruning, Vineyards |
| Authors | |
| Added by: | [] |
| Total mark: | 0 |
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