Open Access
Issue |
E3S Web Conf.
Volume 391, 2023
4th International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED-ICMPC 2023)
|
|
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Article Number | 01055 | |
Number of page(s) | 10 | |
DOI | https://doi.org/10.1051/e3sconf/202339101055 | |
Published online | 05 June 2023 |
- S. Shrimali, PlantifyAI: A Novel Convolutional Neural Network Based Mobile Application for Efficient Crop Disease Detection and Treatment, 2021 2nd Asia Conference on Computers and Communications (ACCC), Singapore, pp. 6–9 (2021) [CrossRef] [Google Scholar]
- L. Shanmugam, A. L. A. Adline, N. Aishwarya and G. Krithika, Disease detection in crops using remote sensing images, 2017 IEEE Technological Innovations in ICT for Agriculture and Rural Development (TIAR), Chennai, India, pp. 112–115 (2017) [CrossRef] [Google Scholar]
- A. Morbekar, A. Parihar and R. Jadhav, Crop Disease Detection Using YOLO, 2020 International Conference for Emerging Technology (INCET), Belgaum, India, pp. 1–5 (2020) [Google Scholar]
- O. Kulkarni, Crop Disease Detection Using Deep Learning, 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), Pune, India, pp. 1–4 (2018) [Google Scholar]
- S. Solanke, P. Mehare, S. Shinde, V. Ingle and S. Zope, IoT Based Crop Disease Detection and Pesting for Greenhouse - A Review, 2018 3rd International Conference for Convergence in Technology (I2CT), Pune, India, pp. 1–4 (2018) [Google Scholar]
- K. He, X. Zhang, S. Ren and J. Sun, Deep Residual Learning for Image Recognition, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, 2016, pp. 770–778 (2016) [Google Scholar]
- S. Sedkaoui, M. Khelfaoui, Classification Algorithms, in Sharing Economy and Big Data Analytics, Wiley, pp.171–194 (2020) [CrossRef] [Google Scholar]
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