Introduces NMCA-aligned L1/L2 LULC schemes and the Loosdorf-MSL benchmark dataset, with Point Transformer V3 reaching 79.4% mIoU on 8 classes and 58.9% on 20 classes, plus gains from multispectral inputs.
International Journal of Remote Sensing, 40, 1 –19
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 2years
2026 2representative citing papers
EDNO redefines pansharpening as a frequency-domain functional mapping that decouples fusion via Euler-inspired polar coordinates into explicit phase-rotation simulation and implicit spectral modeling for improved efficiency.
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3D LULC classification using multispectral LiDAR and deep learning: current and prospective schemes
Introduces NMCA-aligned L1/L2 LULC schemes and the Loosdorf-MSL benchmark dataset, with Point Transformer V3 reaching 79.4% mIoU on 8 classes and 58.9% on 20 classes, plus gains from multispectral inputs.
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Euler-inspired Decoupling Neural Operator for Efficient Pansharpening
EDNO redefines pansharpening as a frequency-domain functional mapping that decouples fusion via Euler-inspired polar coordinates into explicit phase-rotation simulation and implicit spectral modeling for improved efficiency.