Multimodal Remote Sensing Classification on Augsburg HSI+SAR (test) benchmark leaderboard · SOTA2 Research

Multimodal Remote Sensing Classification on Augsburg HSI+SAR (test)

97.78Class Accuracy 1MSFMamba

Evaluation Results

Method	Links
MSFMamba2025.09		97.78	89.61	62.06	94.73	96.63	66.6	77	90.81	83.49	87.13
SS-MAE2025.09		97.52	89.21	75.58	95.56	98.11	71.52	80.98	91.73	86.93	88.4
HLMamba2025.09		97.51	89.07	35.54	96.25	93.68	89.32	81.26	90.31	83.23	86.41
BDGF2025.09		97.03	91.74	87.28	96.13	97.2	84.06	77.41	93.57	90.12	90.93
MACN2025.09		96.84	86.89	73.21	94.48	96.42	61.55	79.3	89.98	84.1	86.01
Fusion-HCT2025.09		96.32	85.89	78.81	94.32	96.84	62.72	74.2	89.65	84.15	85.6
CALC2025.09		95.67	89.96	51.37	90.04	55.79	96.5	76.85	88.79	79.46	84.29
AsyFFNet2025.09		94.32	85.8	85.28	91.51	96.84	69.64	82.66	88.91	86.58	84.62
UACL2025.09		93.51	89.94	64.09	95.79	95.3	90.03	77.45	91.09	86.59	87.53
NCGLF2025.09		92.32	89.55	70	94.38	93.96	73.4	80.03	90.23	84.81	86.37