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Table 5 Classification performance of the model proposed in this study compared with traditional algorithms

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

Category Index BP HOG SIFT LBP COLOR CL TFNet
Buddha Precision 56.44 39.66 47.14 51.61 42.65 62.00 72.22
Recall rate 55.23 37.19 46.52 48.49 40.92 61.06 70.18
F1-score 55.83 38.39 46.83 50.00 41.77 61.53 71.19
Bodhisattva Precision 56.52 37.61 43.87 49.78 39.37 37.25 81.44
Recall rate 55.01 35.62 41.99 48.03 37.67 35.08 80.04
F1-score 55.75 36.59 42.91 48.89 38.50 36.13 80.73
Disciple Precision 50.69 27.63 31.93 42.98 40.57 38.20 45.90
Recall rate 48.69 27.00 30.46 40.91 37.68 37.01 45.01
F1-score 49.67 27.31 31.18 41.92 39.07 37.60 45.45
Secular person Precision 63.16 25.45 42.90 25.97 39.80 50.90 91.14
Recall rate 61.54 23.69 42.11 23.92 37.56 49.09 89.57
F1-score 62.34 24.54 42.50 24.90 38.65 49.98 90.35
Animal Precision 49.31 47.35 26.36 45.63 37.08 40.49 70.97
Recall rate 48.92 45.66 25.10 43.99 35.72 38.88 69.15
F1-score 49.11 46.49 25.71 44.79 36.39 39.67 70.05
Plant Precision 60.57 34.68 30.88 47.01 29.25 40.23 61.25
Recall rate 58.46 32.17 28.55 46.03 28.11 38.93 60.98
F1-score 59.50 33.38 29.67 46.51 28.67 39.57 61.11
Building Precision 56.31 11.65 35.81 42.78 31.80 71.11 83.33
Recall rate 55.22 10.01 33.56 39.86 29.53 67.99 82.83
F1-score 55.76 10.77 34.65 41.27 30.62 69.52 83.08
Auspicious cloud Precision 41.41 43.10 29.17 47.26 27.81 30.25 90.91
Recall rate 40.03 42.14 27.60 45.62 26.59 28.96 90.04
F1-score 40.71 42.61 28.36 46.43 27.19 29.59 90.47
Average Precision 54.61 33.68 35.96 43.66 36.04 45.74 80.64
Recall rate 53.29 31.84 34.06 41.59 35.13 43.52 78.06
F1-score 53.94 32.73 34.98 42.60 35.58 44.60 78.63
  1. The maximum value of precision rate, recall rate and F1-score for each class of all models are in italics
  2. CL: fused vector of color and texture features