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PolSAR Image Classification on Flevoland (test)

99.65Water Accuracy

DDF2Pol

Updated 1mo ago

Evaluation Results

Method	Links
DDF2Pol 2026.04		99.65	99.52	98.49	95.54	97.96	93.55	96.7	99.29	99.26	98.45	98.2	98.55	99.6	98.3	100	98.16	98.2	97.99
3D-CNN 2026.04		99.05	98.45	96.97	84.84	91.23	82.55	71.2	98.15	98.77	25.82	85.44	98.31	97.53	98.78	100	89.7	88.47	88.73
CV-2D-3D 2026.04		98.41	93.42	97.49	87.44	81.95	89.22	94.16	95.56	98.45	98.13	96.42	91.81	95.1	97.76	100	93.6	94.35	93.01
HybridCVNet 2026.04		97.55	99.6	97.81	97.84	94.69	93.84	90.14	98.81	99.6	97.55	96.45	99.21	99.59	97.22	100	96.7676	97.3313	96.4711
WaveletCNN 2026.04		97.25	97.63	98.63	83.92	95.65	91.54	77.84	96.4	99.39	98.89	96.47	84.29	99.12	99.39	99.48	93.78	94.39	93.21
PolSARFormer 2026.04		97.04	97.22	97.22	90.29	94.48	91.76	84.7	98.42	96.81	97.97	90.67	95.95	97.44	98.29	100	94.41	95.22	93.9
3D-CV-CNN 2026.04		95.68	99.32	91.38	72.98	94.34	90.71	87.28	90.4	98.47	95.79	88.57	88.5	95.12	98.05	98.79	92.17	92.36	91.45