Identification of Plant Stomata Based on YOLO v5 Deep Learning Model
Author:
Affiliation:
1. School of Computer and Information Engineering,Henan University, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3507548.3507560
Reference41 articles.
1. Accelerating Automated Stomata Analysis Through Simplified Sample Collection and Imaging Techniques
2. Stomatal behavior following mid- or long-term exposure to high relative air humidity: A review
3. The Role of Proteases in Determining Stomatal Development and Tuning Pore Aperture: A Review
4. Genotypic and phenotypic differences in fresh weight partitioning of cut rose stems: implications for water loss
5. Using artificial lighting based on electricity price without a negative impact on growth, visual quality or stomatal closing response in Passiflora
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