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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

The maximum value of precision rate, recall rate and F1-score in all models are in italics

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