Soodeh Nikan

1 month ago | journals.plos.org | Kimia Aghamohammadesmaeilketabforoosh |Joshua Parfitt |Soodeh Nikan |Joshua Pearce

4. DiscussionThe results of this study highlight the effectiveness of the SwinUNet architecture combined with deep domain confusion (DDC) techniques for segmenting ripe and unripe strawberries from synthetic training data. To contextualize these results, this approach can be compared with existing state-of-the-art segmentation models commonly used in agricultural applications.