文章基本信息

标题：Algorithm for recognizing and measuring parameters of biological objects in agriculture based on deep learning convolutional neural networks
其他标题：Algorithm for recognizing and measuring parameters of biological objects in agriculture based on deep learning convolutional neural networks
本地全文：下载
作者：Rashid Kurbanov ; Nazhmudin Bugaev ; Alexandr Meshkov 等
期刊名称：E3S Web of Conferences
印刷版ISSN：2267-1242
电子版ISSN：2267-1242
出版年度：2020
卷号：217
页码：10006
DOI：10.1051/e3sconf/202021710006
出版社：EDP Sciences
摘要：As of today existing techniques and tools for measuring leaf area involve the detachment of leaves for further scanning and calculations to determine leaf area. The disadvantages of existing solutions for determining the area of the sheet surface are labor intensity, the duration of these studies, the relatively low accuracy of measurements. Due to these facts this study is an important work aimed to simplifying the process of analyzing biological parameters and other important characteristics of plants, as well as increasing the efficiency of this agrotechnical task. This work aims developing a set of software tools with trained neural networks to determine whether a photographed leaf belongs to the leaves of a soybean crop, assess the health of soybean plants and determine the surface area of a soybean leaf with geotagging.