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AIOT Machine Learning on Medical Imaging Application
Volume: 66 | Article ID: jist1078
Image
Machine Learning-based Whitefly Feature Identification and Counting
  DOI :  10.2352/J.ImagingSci.Technol.2022.66.1.010401  Published OnlineJanuary 2022
Abstract
Abstract

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.

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  Cite this article 

Kai-Chao Yao, Shih-Feng Fu, Wei-Tzer Huang, Cheng-Chun Wu, "Machine Learning-based Whitefly Feature Identification and Countingin Journal of Imaging Science and Technology,  2022,  pp 010401-1 - 010401-9,  https://doi.org/10.2352/J.ImagingSci.Technol.2022.66.1.010401

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  Copyright statement 
Copyright © Society for Imaging Science and Technology 2022
  Article timeline 
  • received January 2021
  • accepted March 2021
  • PublishedJanuary 2022

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