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Models/SGDSCNet

SGDSCNet

Reported on 6 benchmarks across 3 tasks · 1 paper · 3 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision6 results

HyperspectralonIndian Pines
Overall Accuracy· 2025-04-06
99.9
best: 99.94 (KANet)
SOTA
Spatial-Geometry Enhanced 3D Dynamic Snake Convolutional Neural Network for Hyperspectral Image Classification arXiv:2504.04463
Image ClassificationonIndian Pines
Overall Accuracy· 2025-04-06
99.9
best: 99.94 (KANet)
SOTA
Spatial-Geometry Enhanced 3D Dynamic Snake Convolutional Neural Network for Hyperspectral Image Classification arXiv:2504.04463
Hyperspectral Image SegmentationonIndian Pines
Overall Accuracy· 2025-04-06
99.9
best: 99.94 (KANet)
SOTA
Spatial-Geometry Enhanced 3D Dynamic Snake Convolutional Neural Network for Hyperspectral Image Classification arXiv:2504.04463
HyperspectralonPavia University
Overall Accuracy· 2025-04-06
99.99
best: 100 (JigsawHSI)
Spatial-Geometry Enhanced 3D Dynamic Snake Convolutional Neural Network for Hyperspectral Image Classification arXiv:2504.04463
Image ClassificationonPavia University
Overall Accuracy· 2025-04-06
99.99
best: 100 (JigsawHSI)
Spatial-Geometry Enhanced 3D Dynamic Snake Convolutional Neural Network for Hyperspectral Image Classification arXiv:2504.04463
Hyperspectral Image SegmentationonPavia University
Overall Accuracy· 2025-04-06
99.99
best: 100 (JigsawHSI)
Spatial-Geometry Enhanced 3D Dynamic Snake Convolutional Neural Network for Hyperspectral Image Classification arXiv:2504.04463