Plant Quality Assessment and Disease Identification System Using AI
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-6088-8_62
Reference11 articles.
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2. Wiesner-Hanks T, Wu H, Stewart E, DeChant C, Kaczmar N, Lipson H, Gore Michael A, Nelson Rebecca J (2019) Millimeter-level plant disease detection from aerial photographs via deep learning and crowdsourced data. Front Plant Sci 10. https://doi.org/10.3389/fpls.2019.01550
3. Arsenovic M, Karanovic M, Sladojevic S, Anderla A, Stefanovic D (2019) Solving current limitations of deep learning based approaches for plant disease detection. Symmetry 11(7):939. https://doi.org/10.3390/sym11070939
4. Akhtar A, Khanum A, Khan SA, Shaukat A (2013) Automated plant disease analysis (APDA): performance comparison of machine learning techniques. In: Proceedings of the 11th international conference on frontiers of information technology, Islamabad, Pakistan, 16–18 Dec 2013, pp 60–65
5. Bedi P, Gole P (2021) Plant disease detection using hybrid model based on convolutional autoencoder and convolutional neural network. Artif Intell Agric 5:90–101, ISSN 2589-7217. https://doi.org/10.1016/j.aiia.2021.05.002
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