Open Access
Issue
ITM Web Conf.
Volume 44, 2022
International Conference on Automation, Computing and Communication 2022 (ICACC-2022)
Article Number 03067
Number of page(s) 5
Section Computing
DOI https://doi.org/10.1051/itmconf/20224403067
Published online 05 May 2022
  1. K. Zhang, Q. Wu, A. Liu, and X. Meng, “Can deep learning identify tomato leaf disease?”, Advances in Multimedia, vol. 2018 (2018) [Google Scholar]
  2. 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]
  3. 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]
  4. 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]
  5. 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]
  6. K. Simonyan and A. Zisserman, “Very deep convolutional networks for large-scale image recognition,” arXiv preprint arXiv:1409.1556 (2014) [Google Scholar]
  7. 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]
  8. 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]
  9. Plant Village Dataset- Dataset of diseased plant leaf images and corresponding labels https://github.com/spMohanty/PlantVillage-Dataset [Google Scholar]
  10. https://neurohive.io/wp-content/uploads/2018/10/AlexNet-1.png [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.