Academic Sources
References
Selected sources supporting machine learning, IoT, irrigation and plant disease recognition.
- A. Kamilaris and F. X. Prenafeta-Boldu, "Deep learning in agriculture: A survey," Computers and Electronics in Agriculture, vol. 147, pp. 70-90, 2018.
- K. G. Liakos et al., "Machine learning in agriculture: A review," Sensors, vol. 18, no. 8, p. 2674, 2018.
- M. Ayaz et al., "Internet-of-Things-based smart agriculture," IEEE Access, vol. 7, pp. 129551-129583, 2019.
- S. P. Mohanty, D. P. Hughes and M. Salathe, "Using deep learning for image-based plant disease detection," Frontiers in Plant Science, vol. 7, p. 1419, 2016.
- E. C. Too et al., "A comparative study of fine-tuning deep learning models for plant disease identification," Computers and Electronics in Agriculture, vol. 161, pp. 272-279, 2019.
- N. K. Nawandar and V. R. Satpute, "IoT based low cost and intelligent module for smart irrigation system," Computers and Electronics in Agriculture, vol. 162, pp. 979-990, 2019.
- J. G. A. Barbedo, "Factors influencing the use of deep learning for plant disease recognition," Biosystems Engineering, vol. 172, pp. 84-91, 2018.
- Food and Agriculture Organization of the United Nations, The State of the World’s Land and Water Resources for Food and Agriculture, Rome: FAO, 2021.