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Table 3 Comparisons with traditional algorithms in terms of the precision rate, recall rate and F1-score

From: Mural classification model based on high- and low-level vision fusion

Network Precision rate/% Recall rate/% F1-score/%
TFNet 80.64 78.06 78.63
AlexNet-F 75.18 74.65 74.91
VGGNet-F 76.64 76.59 76.61
GoogLeNet-F 73.65 72.23 72.93
ResNet-F 74.51 74.42 74.46
VGGNet-RCC 60.33 58.71 59.51
  1. The maximum value of precision rate, recall rate and F1-score in all models are in italics