NCAM is a hierarchical Bayesian model using neural networks and conjugate Gaussian inference to learn sensor-specific biases for unsupervised multi-source regression, with added conformal prediction for coverage guarantees.
Cocoon: Robust Multi-Modal Perception with Uncertainty-Aware Sensor Fusion.arXiv2024
2 Pith papers cite this work. Polarity classification is still indexing.
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LER-YOLO reports 89.7% AP50 on the MBU benchmark for misaligned RGB-IR UAV detection by routing among RGB-dominant, IR-dominant, and fusion experts using a spatial reliability map.
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Neural Conjugate Aggregation: Identifiable Unsupervised Multi-Sensor Regression under Heterogeneous Sensor Bias
NCAM is a hierarchical Bayesian model using neural networks and conjugate Gaussian inference to learn sensor-specific biases for unsupervised multi-source regression, with added conformal prediction for coverage guarantees.
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LER-YOLO: Reliability-Aware Expert Routing for Misaligned RGB-Infrared UAV Detection
LER-YOLO reports 89.7% AP50 on the MBU benchmark for misaligned RGB-IR UAV detection by routing among RGB-dominant, IR-dominant, and fusion experts using a spatial reliability map.