Spatial federated learning model for identification of corn leaf diseases-Reference-Cited by-同舟云学术

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Spatial federated learning model for identification of corn leaf diseases

Published:2023-07-24 Issue: Volume: Page:
ISSN:2366-3286
Container-title:Spatial Information Research
language:en
Short-container-title:Spat. Inf. Res.

Author:

Patil Nilam Sachin,Kannan E.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computers in Earth Sciences,Computer Science Applications,Geography, Planning and Development

Link

https://link.springer.com/content/pdf/10.1007/s41324-023-00538-w.pdf

Reference28 articles.

1. Tiwari, R. K. (2020). Human age estimation using machine learning techniques. International Journal of Electronics Engineering and Application, 8(1), 1–9.

2. Kaur, M., Kadam, S., & Hannoon, N. (2022). Multi-level parallel scheduling of dependent-tasks using graph-partitioning and hybrid approaches over edge-cloud. Soft Computing, 26, 5347–5362.

3. De Rossi, R. L., et al. (2022). Crop damage, economic losses, and the economic damage threshold for northern corn leaf blight. Crop Protection, 154, 105901.

4. Kaur, M. (2023). AI- and IoT-based energy saving mechanism by minimizing hop delay in multi-hop and advanced optical system based optical channels. Optical and Quantum Electronics, 55, 635.

5. Wang, T., Zhang, F., Gu, H., et al. (2023). A research study on new energy brand users based on principal component analysis (PCA) and fusion target planning model for sustainable environment of smart cities. Sustainable Energy Technologies and Assessments, 57, 103262.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Federated Learning for Collaborative Crop Disease Monitoring in Wheat Production;2023 2nd International Conference on Multidisciplinary Engineering and Applied Science (ICMEAS);2023-11-01

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