Introduces a two-stream attention fusion model and joint loss for multispectral point cloud classification, releasing two new airborne datasets and reporting gains over prior methods.
An Intensity -Independent Stereo Registration Method of Push -Broom Hyperspectral Scanner and LiDAR on UAV Platforms,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Proposes a prior-free anomaly detection framework for sub-canopy UAV multispectral point clouds that estimates solar angle via inverse optimization and uses illumination-consistent background dictionaries to separate targets from shadows.
citing papers explorer
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An Enhanced Geometric-Spectral Feature Learning Framework for Airborne Multispectral Point Cloud Classification
Introduces a two-stream attention fusion model and joint loss for multispectral point cloud classification, releasing two new airborne datasets and reporting gains over prior methods.
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Illumination-Invariant Anomaly Detection for Sub-Canopy UAV Multispectral Point Clouds
Proposes a prior-free anomaly detection framework for sub-canopy UAV multispectral point clouds that estimates solar angle via inverse optimization and uses illumination-consistent background dictionaries to separate targets from shadows.