论文标题
一个博学的模拟环境，以模拟室内耕作的植物生长
A Learned Simulation Environment to Model Plant Growth in Indoor Farming
论文作者
论文摘要
我们开发了一个模拟器，以量化环境参数变化对精确耕作中植物生长的影响。我们的方法将植物图像的处理与深度卷积神经网络（CNN），增长曲线建模和机器学习结合在一起。结果，我们的系统能够基于环境变量来预测增长率，这为多功能增强学习剂的发展打开了大门。
We developed a simulator to quantify the effect of changes in environmental parameters on plant growth in precision farming. Our approach combines the processing of plant images with deep convolutional neural networks (CNN), growth curve modeling, and machine learning. As a result, our system is able to predict growth rates based on environmental variables, which opens the door for the development of versatile reinforcement learning agents.
