Wheat leaf disease classification using modified ResNet50 convolutional neural network model
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-18049-z.pdf
Reference51 articles.
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2. Trivelli L, Apicella A, Chiarello F, Rana R, Fantoni G, Tarabella A (2019) From precision agriculture to Industry 4.0: unveiling technological connections in the agrifood sector. Br Food J 121(8):1730–1743. https://doi.org/10.1108/BFJ-11-2018-0747
3. Subeesh A, Mehta CR (2021) Automation and digitization of agriculture using artificial intelligence and internet of things. Artif Intell Agric 5:278–291. https://doi.org/10.1016/j.aiia.2021.11.004
4. Figueroa M, Hammond-Kosack KE, Solomon PS (2018) A review of wheat diseases—a field perspective. Mol Plant Pathol 19(6):1523–1536. https://doi.org/10.1111/mpp.12618
5. Noon SK, Amjad M, Qureshi MA, Mannan A (2020) Use of deep learning techniques for identification of plant leaf stresses: a review. Sustain Comput: Inform Syst 28:100443. https://doi.org/10.1016/j.suscom.2020.100443
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