A spectral framework for nonlinear DR uses spectral bases plus cross-entropy optimization to create multi-scale embeddings that preserve both global manifold geometry and local neighborhoods while supporting graph-frequency analysis.
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A systematic review that introduces a framework for feature extraction in remote sensing, traces its evolution in the data value chain, and synthesizes trends toward unified representations and foundation models.
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A Spectral Framework for Multi-Scale Nonlinear Dimensionality Reduction
A spectral framework for nonlinear DR uses spectral bases plus cross-entropy optimization to create multi-scale embeddings that preserve both global manifold geometry and local neighborhoods while supporting graph-frequency analysis.
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Feature Extraction in the Remote Sensing Data Value Chain: A Systematic Review of Methods and Applications
A systematic review that introduces a framework for feature extraction in remote sensing, traces its evolution in the data value chain, and synthesizes trends toward unified representations and foundation models.