Hyperspectral Image Classification On Casi

Overall Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

		Paper Title
SSDGL	95.36	A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image Classification
AMS-M2ESL	88.82±0.93%	Adaptive Mask Sampling and Manifold to Euclidean Subspace Learning with Distance Covariance Representation for Hyperspectral Image Classification
FPGA	86.61	FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification
CVSSN	82.55±0.47%	Exploring the Relationship between Center and Neighborhoods: Central Vector oriented Self-Similarity Network for Hyperspectral Image Classification

0 of 4 row(s) selected.