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Table 5 Patch-level ACA (%) for Different Categories of Different Datasets

From: Reverse active learning based atrous DenseNet for pathological image classification

  BACH CCG UCSB
  Nor. Ben. C. in situ I. car. Nor. L. I L. II L. III Ben. Mal.
AlexNet [1] 92.13 90.18 89.52 91.25 95.16 93.68 95.82 42.43 94.81 92.75
VGG-16 [10] 90.96 93.84 89.46 92.89 98.71 96.36 98.06 65.61 98.32 96.58
ResNet-50 [12] 92.29 94.50 92.29 91.61 87.54 99.10 92.87 50.32 97.48 96.16
ResNet-101 [12] 91.96 89.20 90.66 92.88 85.46 98.32 99.88 50.45 98.07 95.49
DenseNet [13] 94.61 91.50 95.73 93.82 92.04 98.05 96.97 50.08 96.97 96.60
ADN (ours) 96.30 92.36 93.50 94.23 99.18 97.70 99.52 70.68 98.54 96.73
  1. Best accuracy is in Bold.