Data from: StomataCounter: a neural network for automatic stomata identification and counting

Karl C. Fetter, Sven Eberhardt, Rich S. Barclay, Scott Wing & Stephen R. Keller
Stomata regulate important physiological processes in plants and are often phenotyped by researchers in diverse fields of plant biology. Currently, there are no user friendly, fully-automated methods to perform the task of identifying and counting stomata, and stomata density is generally estimated by manually counting stomata. We introduce StomataCounter, an automated stomata counting system using a deep convolutional neural network to identify stomata in a variety of different microscopic images. We use a human-in-the-loop approach...
1 citation reported since publication in 2019.
269 views reported since publication in 2019.

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60 downloads reported since publication in 2019.

These counts follow the COUNTER Code of Practice, meaning that Internet robots and repeats within a certain time frame are excluded.
What does this mean?