Robust Accuracy on Salinas (Hyperspectral Image Classification) benchmark leaderboard · SOTA2 Research

Robust Accuracy on Salinas (Hyperspectral Image Classification)

99.92Benign AccuracyS3ANet

Evaluation Results

Method	Links
S3ANet2025.10		99.92	89.16	95.88
S3ANet2025.10		99.92	89.16	95.88
S3ANet2025.10		99.89	91.73	96.2
S3ANet2025.10		99.89	91.73	96.2
S3ANet2025.10		99.71	95.68	98.83
RCCA2025.10		99.68	91.69	97.95
RCCA2025.10		99.68	91.69	97.95
RCCA2025.10		99.52	65.01	68.67
RCCA2025.10		99.52	65.01	68.67
SpaFCN2025.10		99.5	77.35	79.65
SpaFCN2025.10		99.5	77.35	79.65
SACNet2025.10		99.46	72.31	86.62
SACNet2025.10		99.46	72.31	86.62
SSFCN2025.10		99.2	31.78	43.42
SSFCN2025.10		99.2	31.78	43.42
RCCA2025.10		99.1	68.07	73.04
DilatedFCN2025.10		98.51	72.8	88.3
DilatedFCN2025.10		98.51	72.8	88.3
SpaFCN2025.10		97.54	69.29	71.5
SpaFCN2025.10		97.54	69.29	71.5
SSFCN2025.10		97.41	26.82	55.03
SACNet2025.10		96.91	69.82	77.23
SACNet2025.10		96.91	69.82	77.23
DilatedFCN2025.10		96.52	51.98	69.47
SpaFCN2025.10		96.46	71.97	74.54
DilatedFCN2025.10		96.2	50.72	57
DilatedFCN2025.10		96.2	50.72	57
SACNet2025.10		96.11	80.59	86.27
SSFCN2025.10		94.62	15.14	31.8
SSFCN2025.10		94.62	15.14	31.8