FSANet: A Lightweight Network for Tobacco Grouping Using Multi-scale Convolution and Attention Mechanism
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-1332-5_26
Reference24 articles.
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3. Yang, S., Dong, C., Wang, F., Zhou, M., Yuan, M., Huang, J.: Fisher's tobacco leaf grading method based on image multi-features. In: 2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT), September 2022. https://doi.org/10.1109/aicit55386.2022.9930167
4. Harjoko, A., Prahara, A., Supardi, T.W., Candradewi, I., Pulungan, R., Hartati, S.: Image processing approach for grading tobacco leaf based on color and quality. Int. J. Smart Sens. Intell. Syst. 12(1), 1 (2019). https://doi.org/10.21307/ijssis-2019-010
5. Lin, J., et al.: CAMFFNet: a novel convolutional neural network model for tobacco disease image recognition. Comput. Electron. Agric. 107390 (2022). https://doi.org/10.1016/j.compag.2022.107390
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