Table 5 Comparison of accuracies under different algorithms
From: Ancient mural classification methods based on a multichannel separable network
Reference [12] | Reference [13] | Reference [14] | GoogLeNet | VGG | MCSN | |
|---|---|---|---|---|---|---|
Animals | 65.63%/75.89%/65.13% | 64.16%/73.56%/66.22% | 66.61%/75.61%/60.61% | 67.34%/67.34%/67.34% | 70.63%/67.34%/67.34% | 75.16%/82.16%/75.16% |
Buildings | 61.13%/72.54%/64.28% | 63.51%/79.98%/73.24% | 64.55%/77.45%/68.35% | 65.98%/74.26%/68.33% | 66.31%/68.43%/64.25% | 69.45%/75.35%/70.24% |
Clouds | 68.24%/85.69%/76.22% | 70.24%/84.67%/72.67% | 70.36%/88.69%/74.65% | 72.35%/84.34%/73.25% | 74.64%/84.01%/72.59% | 77.38%/90.36%/79.31% |
Disciples | 63.35%/88.54%/70.13% | 69.41%/84.68%/74.61% | 66.63%/87.19%/74.04% | 62.31%/78.83%/76.21% | 65.56%/77.21%/71.06% | 70.33%/81.03%/78.61% |
fo | 61.34%/79.24%/76.13% | 64.98%/82.44%/72.14% | 67.15%/89.36%/77.24% | 69.21%/86.54%/74.48% | 64.58%/78.87%/71.69% | 73.25%/87.36%/76.39% |
People | 62.33%/75.33%/66.16% | 67.27%/81.49%/72.46% | 67.20%/84.31%/71.89% | 70.16%/81.59%/72.31% | 69.24%/79.21%/71.59% | 69.07%/78.82%/75.56% |
Plants | 67.19%/83.16%/69.35% | 65.18%/75.84%/67.94% | 68.85%/82.16%/69.71% | 68.21%/82.41%/69.61% | 61.55%/72.46%/69.21% | 70.22%/86.66%/73.21% |
pusa | 69.99%/87.25%/76.41% | 66.64%/89.66%/71.97% | 71.45%/79.97%/74.69% | 66.29%/83.46%/71.24% | 67.15%/70.05%/67.16% | 68.11%/91.00%/73.21% |