基于人工智能的二维和三维葡萄园产量预测系统的对比分析

IF 2.4 4区 农林科学 Q2 AGRICULTURAL ENGINEERING
Dhanashree Barbole, Parul M. Jadhav
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引用次数: 0

摘要

传统的估算酒庄葡萄簇重量的技术,通常包括手动计算每棵葡萄树的葡萄簇的种类,并通过整个葡萄树的种类进行缩放。这种方法可能是费力的,昂贵的,其准确性取决于样品的规模。为了克服这些问题,提出了基于计算机视觉(CV)、深度学习(DL)和机器学习(ML)的葡萄园产量预测系统的混合方法。自行准备的数据集用于葡萄园的2D和3D产量预测系统的比较分析。采用基于ml的方法对D435I相机创建的RGB-D图像数据集进行分割操作,并利用这些数据集对单幅图像中的葡萄簇进行基于ml的权重预测技术。将基于dl的Keras回归模型与各种基于ml的回归模型进行权重预测任务的对比分析,最后提出一个预测模型来估算整个葡萄园的产量。分析表明,与2D产量预测系统相比,3D产量预测系统的性能有所提高,葡萄簇分割像素精度可达94.81%,产量预测精度可达99.58%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative analysis of 2D and 3D vineyard yield prediction system using artificial intelligence
Traditional techniques for estimating the weight of clusters in a winery, generally consist of manually counting the variety of clusters per vine, and scaling by means of the entire variety of vines. This method can be arduous, costly, and its accuracy is dependent on the scale of the sample. To overcome these problems, hybrid approaches of Computer Vision (CV), Deep Learning (DL) and Machine Learning (ML) based vineyard yield prediction systems are proposed. Self-prepared datasets are used for comparative analysis of 2D and 3D yield prediction systems for vineyards. DL-based approach for segmentation operation on an RGB-D image dataset created with the D435I camera is used along with the ML-based weight prediction technique of grape clusters present in the single image is employed using these datasets. A comparative analysis of the DL-based Keras regression model and various ML-based regression models for the weight prediction task is taken into account, and finally a prediction model is proposed to estimate the yield of the entire vineyard. The analysis shows improved performance with the 3D vineyard yield prediction system compared to the 2D vineyard yield prediction system with grape cluster segmentation pixel accuracy upto 94.81% and yield prediction accuracy upto 99.58%.
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来源期刊
Journal of Agricultural Engineering
Journal of Agricultural Engineering AGRICULTURAL ENGINEERING-
CiteScore
2.30
自引率
5.60%
发文量
40
审稿时长
10 weeks
期刊介绍: The Journal of Agricultural Engineering (JAE) is the official journal of the Italian Society of Agricultural Engineering supported by University of Bologna, Italy. The subject matter covers a complete and interdisciplinary range of research in engineering for agriculture and biosystems.
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