Publisher
Springer Nature Singapore
Reference18 articles.
1. McCraine, C.D., Samiappan, S., Czarnecki, J.M.P., Darrin, M.D.: Plant density estimation and weeds mapping on row crops at emergence using low altitude UAS imagery. In: Proceedings, vol. 11008, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IV, p. 110080Y (2019). https://doi.org/10.1117/12.2520252
2. Hoffman, N., Singels, A.: Evaluating the use of aerially captured spectral data for characterising drought-tolerance traits in sugarcane. In: 41st Annual Conference—Australian Society of Sugar Cane Technologists, vol. 41, pp. 41–51, 462019 (2019). https://doi.org/10.1011/as2520252
3. Ganesh, B.R., Chellaswamy, C.: Different stages of disease detection in squash plant based on machine learning. J. Biosci. 47, 54–66 (2022). https://doi.org/10.1007/s12038-021-00241-8
4. Lobachevsky, Ya.P., Dorokhov, A.S.: Promising scientific and technical projects in the field of mechanization and robotization of agriculture. In: Formation of a Single Scientific and Technological Space of the Union State: Problems, Prospects, Innovations, pp. 333–343 (2017)
5. Lachuga, Yu., Izmailov, A., Lobachevsky, Ya., Shogenov, Yu.: Development of intensive machine technologies, robotic equipment, efficient energy supply and digital systems in the agro-industrial complex. Mach. Equip. Village 6 (264), 2–9 (2019)