File:Fig4 Sutton SmartAgTech2023 3.jpg
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Summary
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. |
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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 |
Other versions |
Licensing
|
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
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current | 22:50, 26 December 2023 | 3,238 × 803 (291 KB) | Shawndouglas (talk | contribs) |
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