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home/Knowledge Base/CODES/Multi-modal/Geometric Multimodal Learning Based on Local Signal Expansion for Joint Diagonalization

Geometric Multimodal Learning Based on Local Signal Expansion for Joint Diagonalization

January 25, 2021

Geometric Multimodal Learning Based on Local Signal Expansion for Joint Diagonalization
M. Behmanesh, P. Adibi, J. Chanussot, C. Jutten and S. M. S. Ehsani,

IEEE Transactions on Signal Processing
doi: 10.1109/TSP.2021.3053513.

https://github.com/maysambehmanesh/m-LSEJD

 

Tags:dimensionality reductionintrinsic tangent spaceLaplacian matrices joint diagonalizationmanifold learningmultimodal signal processing
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Categories
  • CODES
    • Anomaly
    • Change Detection
    • Classification of Hyperspectral Images
    • Classification of Remote Sensing Data
    • Data fusion: hyperspectral + Lidar
    • Data fusion: Hyperspectral + Multispectral
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  Graph Learning Based on Signal Smoothness Representation for Homogeneous and Heterogeneous Change Detection

CoSpace: Common Subspace Learning from Hyperspectral-Multispectral Correspondences  

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