农业无人机智能机器学习系统——基于人工智能和深度学习

Intelligent Machine Learning System of Agricultural UAV Based on Artificial Intelligence and Deep Learning

为了提高农业无人机作业时的自主学习能力,基于人工智能技术将深度学习算法应用到了无人机机器学习系统的设计上,并提出了基于神经网络深度学习的农业无人机智能识别系统,有效提高了无人机的自动学习和识别能力。以采摘机器人的设计为例,对智能机器学习系统的可靠性进行了验证,并对不同学习算法果实识别的准确性进行了测试。测试结果表明:基于神经网络的深度学习算法在果实的成熟度识别方面具有明显的优势,从而验证了算法的可靠性。

In order to improve the autonomous learning ability of agricultural UAV,based on artificial intelligence technology,the deep learning algorithm is applied to the design of UAV machine learning system.And it proposed an intelligent recognition system of agricultural UAV based on neural network deep learning,which effectively improves the automatic learning and recognition ability of UAV.Taking the design of picking robot as an example,it verified the reliability of intelligent machine learning system,and it tested the accuracy of fruit recognition of different learning algorithms.The test results show that it has obvious advantages for the deep learning algorithm based on neural network in fruit maturity recognition,which verifies the reliability of the algorithm.