Study of Image Classification Accuracy with Fourier Ptychography

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

2 Scopus Citations
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Author(s)

  • Hongbo Zhang
  • Yaping Zhang
  • Lin Wang
  • Zhijuan Hu
  • Wenjing Zhou
  • Deng Cao
  • Ting-Chung Poon

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number4500
Journal / PublicationApplied Sciences (Switzerland)
Volume11
Issue number10
Online published14 May 2021
Publication statusPublished - May 2021

Link(s)

Abstract

In this research, the accuracy of image classification with Fourier Ptychography Microscopy (FPM) has been systematically investigated. Multiple linear regression shows a strong linear relation-ship between the results of image classification accuracy and image visual appearance quality based on PSNR and SSIM with multiple training datasets including MINST, Fashion MNIST, Cifar, Caltech 101, and customized training datasets. It is, therefore, feasible to predict the image classification accuracy only based on PSNR and SSIM. It is also found that the image classification accuracy of FPM reconstructed with higher resolution images is significantly different from using the lower resolution images under the lower numerical aperture (NA) condition. The difference is yet less pronounced under the higher NA condition.

Research Area(s)

  • Deep learning, Fourier ptychography, Image classification, Neural network

Citation Format(s)

Study of Image Classification Accuracy with Fourier Ptychography. / Zhang, Hongbo; Zhang, Yaping; Wang, Lin et al.
In: Applied Sciences (Switzerland), Vol. 11, No. 10, 4500, 05.2021.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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