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Machine Learning-based Whitefly Feature Identification and Counting

机译:基于机器学习的粉虱特征识别与计数

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摘要

This article uses LabVIEW, a software program to develop a whitefly feature identification and counting technology, and machine learning algorithms for whitefly monitoring, identification, and counting applications. In addition, a high-magnification CCD camera is used for on-demand image photography, and then the functional programs of the VI library of LabVIEW NI-DAQ and LabVIEW NI Vision Development Module are used to develop image recognition functions. The grayscale-value pyramid-matching algorithm is used for image conversion and recognition in the machine learning mode. The built graphical user interface and device hardware provide convenient and effective whitefly feature identification and sample counting. This monitoring technology exhibits features such as remote monitoring, counting, data storage, and statistical analysis. xe00d;c 2022 Society for Imaging Science and Technology.
机译:本文使用LabVIEW(一种软件程序)来开发粉虱特征识别和计数技术,以及用于粉虱监测、识别和计数应用的机器学习算法。此外,使用高倍率CCD相机进行按需图像摄影,然后使用LabVIEW NI-DAQ的VI库和LabVIEW NI Vision Development Module的功能程序来开发图像识别功能。在机器学习模式下,采用灰度值金字塔匹配算法进行图像转换和识别。内置的图形用户界面和设备硬件提供了方便有效的粉虱特征识别和样品计数。该监控技术具有远程监控、计数、数据存储和统计分析等功能。& xe00d;c 2022 影像科学与技术学会。

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