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Table 7 ACA (%) of Different Frameworks for BACH Testing Set

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

  Patch-level Slice-level
  Nor. Ben. C. in situ I. car. Ave. ACA Ave. ACA Pre. Rec. F-mea.
CNN [24] 61.70 56.70 83.30 88.30 72.50 80 79.52 80.00 79.76
CNN+SVM [24] 65.00 61.70 76.70 88.30 72.93 85 86.61 85.00 85.80
AlexNet [1] 60.00 58.33 85.00 95.00 74.58 80 82.86 80.00 81.40
VGG-16 [10] 75.00 61.67 75.00 90.00 75.42 85 86.61 85.00 85.80
ResNet-50 [12] 63.33 65.00 80.00 95.00 75.83 85 86.67 85.00 85.83
ResNet-101 [1] 65.00 70.00 75.00 90.00 75.00 85 87.86 85.00 86.41
DenseNet [13] 66.67 76.67 73.33 88.33 76.25 85 90.00 80.33 84.89
ADN (ours) 60.00 66.67 88.33 93.33 77.08 85 86.67 85.00 85.83
ADN+DRAL (ours) 71.67 73.33 88.33 96.67 82.50 90 92.86 90.00 91.41
  1. Best accuracy is in Bold