Local correntropy matrix representation for hyperspectral image classification
The hyperspectral images (HSIs) classification technique has received widespread attention
in the field of remote sensing. However, how to achieve satisfactory classification …
in the field of remote sensing. However, how to achieve satisfactory classification …
CACFTNet: A Hybrid Cov-Attention and Cross-Layer Fusion Transformer Network for Hyperspectral Image Classification
S Cheng, R Chan, A Du - IEEE Transactions on Geoscience …, 2024 - ieeexplore.ieee.org
Hyperspectral (HS) image classification has become an important research area. Although
previous work on HS image classification has achieved impressive results, finding a proper …
previous work on HS image classification has achieved impressive results, finding a proper …
Locally homogeneous covariance matrix representation for hyperspectral image classification
Combining spectralandspatial information has been proven to be an effective way for
hyperspectral image (HSI) classification. However, making full use of spectral–spatial …
hyperspectral image (HSI) classification. However, making full use of spectral–spatial …
[PDF][PDF] Comparison of Local Kernel and Covariance Matrix Descriptors for Spatial-Spectral Classification of Hyperspectral Images
B Asghari Beirami, M Mokhtarzade - International Journal of Smart …, 2022 - ijsee.ctb.iau.ir
Hyperspectral sensors collect information from the earth's surface in the form of images with
a large number of electromagnetic bands. Accurate classification of hyperspectral images …
a large number of electromagnetic bands. Accurate classification of hyperspectral images …