Stacking ensemble model of deep learning for plant disease recognition
Author:
Funder
Fundamental Research Funds for the Central Universities
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-022-04334-6.pdf
Reference41 articles.
1. Atoum Y, Afridi MJ, Liu X, McGrath JM, Hanson LE (2016) On developing and enhancing plant-level disease rating systems in real fields. Pattern Recognit 53:287–299
2. Barbedo JG (2018) Factors influencing the use of deep learning for plant disease recognition. Biosyst Eng 172:84–91
3. Chen J, Wang W, Zhang D, Zeb A, Nanehkaran YA (2021a) Attention embedded lightweight network for maize disease recognition. Plant Pathol 70(3):630–642
4. Chen J, Zhang D, Suzauddola M, Nanehkaran YA, Sun Y (2021b) Identification of plant disease images via a squeeze-and-excitation MobileNet model and twice transfer learning. IET Image Proc 15(5):1115–1127
5. Chen J, Zhang D, Zeb A, Nanehkaran YA (2021c) Identification of rice plant diseases using lightweight attention networks. Expert Syst Appl 169:1–12
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