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Single-cell conventional pap smear image classification using pre-trained deep neural network architectures.

Mohammed Aliy MohammedFetulhak AbdurahmanYodit Abebe Ayalew
Published in: BMC biomedical engineering (2021)
Even though the size of DenseNet169 is small compared to the experimented pre-trained DCNN image classifiers, yet, it is not suitable for mobile or edge devices. Further experimentation with mobile or small-size DCNN image classifiers is required to extend the applicability of the models in real-world demands. In addition, since all experiments used the SIPaKMeD dataset, additional experiments will be needed using new datasets to enhance the generalizability of the models.
Keyphrases
  • deep learning
  • neural network
  • single cell
  • rna seq
  • resistance training
  • machine learning
  • high throughput
  • mycobacterium tuberculosis