Explainable AI for Next Generation Agriculture—Current Scenario and Future Prospects
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-67450-1_7
Reference38 articles.
1. Pallathadka, H., Mustafa, M., Sanchez, D. T., Sajja, G. S., Gour, S., & Naved, M. (2023). Impact of machine learning on management, healthcare, and agriculture. Materials Today: Proceedings, 80, 2803–2806. https://doi.org/10.1016/j.matpr.2021.07.042
2. https://www.communitywestbank.com/blog/the-importance-of-agriculture-to-the-united-states-economy.php
3. Maqbool, N., Shahid, M. A., & Khan, S. J. (2023). Situational assessment for fecal sludge management in major cities of Pakistan. Environmental Science and Pollution Research, 30(44), 98869–98880. https://doi.org/10.1007/s11356-022-22331-2
4. Lakhwani, K., Gianey, H., Agarwal, N., & Gupta, S. (2019). Development of IoT for smart agriculture: A review. In Emerging Trends in Expert Applications and Security: Proceedings of ICETEAS 2018 (pp. 425–432). https://doi.org/10.1007/978-981-13-2285-3_50.
5. Schönfeld, M. V., Heil, R., & Bittner, L. (2018). Big data on a farm—Smart farming. In Big data in context (pp. 109–120).
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