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Description	Fig. 4 Color figure of segmentation pipeline. Input image patches ① are segmented into trichome glands ② using the artificial neural network DO-U-Net. Outputs from different patches are stitched together ③ to segment trichome gland instances for each image. ④ Glands are then individually classified by phenotype using a k-NN classifier.
Source	Sutton, D.B.; Punja, Z.K.; Hamarneh, G. (2023). "Characterization of trichome phenotypes to assess maturation and flower development in Cannabis sativa L. (cannabis) by automatic trichome gland analysis". Smart Agricultural Technology 3: 100111. doi:10.1016/j.atech.2022.100111.
Date	2023
Author	Sutton, D.B.; Punja, Z.K.; Hamarneh, G.
Permission (Reusing this file)	Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
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