Automated Seed Classification Using State-of-the-Art Techniques
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s42979-024-02759-8.pdf
Reference32 articles.
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3. Wu N, Liu F, Bao Y, Li M, Huang W, Meng F, Zhang C, He Y. Rapid and accurate varieties identification of different crop seeds under sample-limited condition based on hyperspectral imaging and deep transfer learning. 2020. https://doi.org/10.21203/rs.3.rs-108818/v1.
4. Kansiime M, Bundi M, Nicodemus J, Justus O, Marandu D, Njau S, Radegunda K, Williams F, Karanja D, Tambo J, Romney D. Assessing sustainability factors of farmer seed production: a case of the good seed initiative project in Tanzania. Agric Food Secur. 2021;10:15. https://doi.org/10.1186/s40066-021-00289-7.
5. Qiu Z, Chen J, Zhao Y, Zhu S, He Y, Zhang C. Variety identification of single rice seed using hyperspectral imaging combined with convolutional neural network. Appl Sci. 2018;8:212. https://doi.org/10.3390/app8020212.
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