Determination of wheat types using optimized extreme learning machine with metaheuristic algorithms
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-08354-x.pdf
Reference62 articles.
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2. Huebner FR, Bietz JA, Nelsen T et al (1999) Soft wheat quality as related to protein composition. Cereal Chem 76:650–655. https://doi.org/10.1094/CCHEM.1999.76.5.650
3. Sabanci K, Kayabasi A, Toktas A (2017) Computer vision-based method for classification of wheat grains using artificial neural network. J Sci Food Agric 97:2588–2593. https://doi.org/10.1002/jsfa.8080
4. Bao Y, Mi C, Wu N et al (2019) Rapid classification of wheat grain varieties using hyperspectral imaging and chemometrics. Appl Sci 9:4119. https://doi.org/10.3390/app9194119
5. Tian H, Wang T, Liu Y et al (2020) Computer vision technology in agricultural automation —a review. Inf Process Agric 7:1–19. https://doi.org/10.1016/j.inpa.2019.09.006
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