改进的残差式3D-CNN和近邻注意力的高光谱遥感图像分类

潘增滢, 吴瑞姣, 林易丰, 翁谦, 林嘉雯

Hyperspectral remote sensing image classification using improved residual 3D-CNN and neighborhood attention

PAN Zengying, WU Ruijiao, LIN Yifeng, WENG Qian, LIN Jiawen

表4 各个模块的消融对比

Tab.4 Ablation comparison of each module

数据集 精度 Baseline RSFEM NAM RSFEM+NAM IP OA/% 99.04 99.38 99.11 99.39 AA/% 98.31 99.06 98.38 99.06 Kappa 0.989 1 0.993 0 0.989 9 0.993 0 PU OA/% 99.26 99.45 99.30 99.67 AA/% 98.19 98.63 98.34 99.35 Kappa 0.990 2 0.992 7 0.990 7 0.995 6 HO OA/% 98.39 98.53 98.50 98.64 AA/% 98.17 98.13 98.24 98.32 Kappa 0.982 5 0.984 0 0.983 7 0.985 2