112 citations · 159 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 47 cited
Deep reinforcement learning for irrigation scheduling using high-dimensional sensor feedback
Yuji Saikai, Allan Peake, Karine Chenu
Deep reinforcement learning has considerable potential to improve irrigation scheduling in many cropping systems by applying adaptive amounts of water based on various measurements…
q-bio.QM2015★ 112 cited
Assessment of the potential impacts of plant traits across environments by combining global sensitivity analysis and dynamic modeling in wheat
Pierre Casadebaig, Bangyou Zheng, Scott Chapman +3
A crop can be viewed as a complex system with outputs (e.g. yield) that are affected by inputs of genetic, physiology, pedo-climatic and management information. Application of nume…