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.
翻译:我们开发了一个模拟器来量化环境参数变化对精密农业植物生长的影响。 我们的方法是将植物图像的处理与深层进化神经网络(CNN ) 、 增长曲线模型和机器学习结合起来。 结果,我们的系统能够预测基于环境变量的增长率,这为发展多功能强化学习工具打开了大门。