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arabidopsis.pth (186.11 MB)
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barley.pth (186.13 MB)
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pore_measurements.csv (21.23 kB)
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density.csv (0.75 kB)
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SAI Assets v2.0
Version 30 2024-08-26, 01:31
Version 29 2024-05-30, 05:06
Version 28 2024-05-30, 05:04
Version 27 2024-05-30, 05:02
Version 26 2024-05-30, 04:47
Version 25 2024-05-30, 04:45
Version 24 2024-05-30, 02:55
Version 23 2024-05-30, 02:54
Version 22 2024-05-30, 02:53
Version 21 2024-05-30, 02:47
Version 20 2024-05-30, 02:43
Version 19 2024-05-29, 09:30
Version 18 2024-05-29, 07:53
Version 17 2024-05-29, 07:52
Version 16 2024-05-29, 07:39
Version 15 2024-05-29, 07:31
Version 14 2024-05-29, 05:30
Version 13 2024-05-29, 05:29
Version 12 2024-05-26, 12:49
Version 11 2024-05-25, 02:19
online resource
posted on 2024-08-26, 01:31 authored by James BockmanJames Bockman- Using microscopy to investigate stomatal behaviour is common in plant physiology research. Manual inspection and measurement of stomatal pore features is low throughput, relies upon expert knowledge to record stomatal features accurately, requires significant researcher time and investment, and can represent a significant bottleneck to research pipelines.
- To alleviate this, we introduce StomaAI (SAI): a reliable, user-friendly and adaptable tool for stomatal pore and density measurements via the application of deep computer vision, which has been initially calibrated and deployed for the model plant Arabidopsis (dicot) and the crop plant barley (monocot grass).
- SAI is capable of producing measurements consistent with human experts and successfully reproduced conclusions of published datasets.
- SAI boosts the number of images that can be evaluated in a fraction of the time, so can obtain a more accurate representation of stomatal traits than is routine through manual measurement. An online demonstration of SAI is hosted at https://sai.aiml.team, and the full local application is publicly available for free on GitHub through https://github.com/xdynames/sai-app.
