研究文章
多尺度密集Cross-Attention机制与协方差池高光谱图像场景分类
|
| 方法 |
1% |
5% |
10% |
| 办公自动化 |
AA |
卡巴 |
办公自动化 |
AA |
卡巴 |
办公自动化 |
AA |
卡巴 |
|
| AlexNet [23] |
90.88 |
93.72 |
89.77 |
94.05 |
96.64 |
93.42 |
94.26 |
95.67 |
95.29 |
| ResNet [33] |
87.21 |
92.07 |
85.88 |
91.70 |
95.15 |
90.74 |
93.52 |
96.73 |
93.11 |
| DenseNet [34] |
85.52 |
90.81 |
84.12 |
91.03 |
94.36 |
90.05 |
93.14 |
96.12 |
92.17 |
| 普朗[35] |
78.86 |
76.17 |
76.49 |
90.28 |
88.17 |
89.16 |
91.81 |
89.32 |
91.17 |
| FSSFNet [36] |
91.04 |
94.74 |
90.02 |
93.56 |
96.69 |
92.82 |
95.85 |
98.03 |
95.37 |
| SAGP [37] |
90.87 |
94.68 |
89.82 |
92.64 |
95.69 |
91.81 |
94.76 |
97.45 |
94.16 |
| MDCA-CP |
91.45 |
94.84 |
89.98 |
94.51 |
97.11 |
93.24 |
96.15 |
98.11 |
96.21 |
|
|