ITM Web Conf.
Volume 44, 2022International Conference on Automation, Computing and Communication 2022 (ICACC-2022)
|Number of page(s)||5|
|Published online||05 May 2022|
- K. Zhang, Q. Wu, A. Liu, and X. Meng, “Can deep learning identify tomato leaf disease?”, Advances in Multimedia, vol. 2018 (2018) [Google Scholar]
- M. Turkoglu and D. Hanbay, “Plant disease and pest detection using deep learning-based “ features,” Turkish Journal of Electrical Engineering & Computer Sciences, vol. 27, no. 3, pp. 1636–1651 (2019) [CrossRef] [Google Scholar]
- U. P. Singh, S. S. Chouhan, S. Jain, and S. Jain, “Multilayer convolution neural network for the classification of mango leaves infected by anthracnose disease,” IEEE Access, vol. 7, pp. 43721–43729(2019) [CrossRef] [Google Scholar]
- J. Chen, Q. Liu, and L. Gao, “Visual tea leaf disease recognition using a convolutional neural network model,” Symmetry, vol. 11, no. 3, p. 343 (2019) [CrossRef] [Google Scholar]
- A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” Communications of the ACM, vol. 60, no. 6, pp. 84–90 (2017) [CrossRef] [Google Scholar]
- K. Simonyan and A. Zisserman, “Very deep convolutional networks for large-scale image recognition,” arXiv preprint arXiv:1409.1556 (2014) [Google Scholar]
- J. Kaur, R. Chadha, S. Thakur, and E. R. Kaur, “International journal of engineering sciences & research technology a review paper on plant disease detection using image processing and neural network approach” (2016) [Google Scholar]
- S. Kumar and R. Kaur, “Plant disease detection using image processing-a review,” International Journal of Computer Applications, vol. 124, no. 16, (2015) [Google Scholar]
- Plant Village Dataset- Dataset of diseased plant leaf images and corresponding labels https://github.com/spMohanty/PlantVillage-Dataset [Google Scholar]
- https://neurohive.io/wp-content/uploads/2018/10/AlexNet-1.png [Google Scholar]
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