Shengyang Li

Bridging the gap between ANNs and SNNs could revolutionize federated learning on resource-constrained devices, achieving high accuracy without sacrificing efficiency.

By explicitly modeling 3D scene geometry, this UAV geo-localization method achieves meter-level accuracy, outperforming existing approaches that treat perspective distortion as mere noise.

SSMs struggle to segment thin structures because they propagate information across, not along, the target, but this frequency-aware approach realigns serialization to trace the geometry.

By explicitly encoding the structural rigidity of ships, SDF-Net achieves state-of-the-art cross-modal ship re-identification, demonstrating the power of incorporating physical priors to overcome radiometric discrepancies.