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Benchmarks
Hyperspectral Semantic Segmentation on HSI Drive v2.0 (test)
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97.44
Accuracy (mu)
HyperVision
80.3632
84.7966
89.23
93.6634
May 17, 2026
Accuracy (mu)
Accuracy (M)
F1 Score (M)
Jaccard Index (M)
Updated 15d ago
Evaluation Results
Method
Method
Links
Accuracy (mu)
Accuracy (M)
F1 Score (M)
Jaccard Index (M)
HyperVision
Trainable Params=15.7 M
2026.05
97.44
89.67
90.7
83.51
HyperFree
Trainable Params=15.7 M
2026.05
96.56
87.52
88.22
79.75
RU-Net
Trainable Params=21.1 M
2026.05
95.53
77.09
79.36
68.61
U-Net
Trainable Params=17.3 M
2026.05
94.74
75.27
76.7
65.37
DeepLabV3+ (ResNet101)
Trainable Params=58.8 M
2026.05
94.23
73.91
74.98
63.46
DeepLabV3+ (MobileNet)
Trainable Params=5.2 M
2026.05
93.79
73.16
75.5
63.57
CGRSeg (False-color)
Trainable Params=19.1 M
2026.05
81.02
48.19
58.06
40.96
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