Toshiba AI Technology Catalog

  • Media data analysis

Unsupervised image clustering: IDFD

Realizes strong performance on inspection image clustering at manufacturing site, and reduces costs of visual checking and manual data analysis.


  • Accuracy for unsupervised clustering of public image data sets increased from 62.3% to 81.5% (the state-of-the-art perfirmance).
  • Achieves highly accurate unsupervised clustering by learning feature preferable for clustering from complex images.

Applications



  • Inspection images in semiconductor manufacturing
  • Visual Inspection images in the manufacturing field

Benchmarks, strengths, and track record



  • Achieved unsupervised clustering accuracy of 81.5% and 95.4% respectively for CIFAR-10 and ImageNet-10 image data sets (62.3% and 71.0% using conventional methods)
  • Achieved state-of-the-art unsupervised image clustering accuracy; adopted at ICLR2021

Inquiries



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