卷积神经网络在土壤理化性质测定中的研究进展
Research Progress of Convolutional Neural Network in Determination of Soil Physical and Chemical Properties

随着农业科技的进步和土壤管理的重要性日益凸显，对土壤理化性质的准确测定和预测变得越来越重要。传统的土壤分析方法通常需要耗费大量的时间和人力，并且受到人为因素的影响。近年来，卷积神经网络(Convolutional Neural Network, CNN)作为一种强大的机器学习方法，在图像处理和模式识别领域取得了巨大成功。本文旨在综述卷积神经网络在土壤理化性质测定中的研究进展，探讨其在土壤科学领域的应用前景。
With the progress of agricultural science and technology and the increasing importance of soil management, the accurate determination and prediction of soil physical and chemical properties become more and more important. Traditional soil analysis methods usually consume a lot of time and manpower, and are affected by human factors. In recent years, convolutional neural network (CNN), as a powerful machine learning method, has achieved great success in image processing and pattern recognition. This paper aims to review the research progress of convolutional neural network in the determination of soil physical and chemical properties, and discuss its application prospects in the field of soil science.