2 citations · 2 across the 5 of their papers we have counts for
7 papers
SC-Match: Scale-Space Matching with Context Consistency for Side-Scan Sonar Mapping
Can Lei, Rafael Garcia, Nuno Gracias +2
Reliable estimation of spatial correspondences between overlapping side-scan sonar (SSS) measurements is essential for mapping, but acoustic appearance variations, weak seabed text…
Geometric Correction of Side-Scan Sonar Images with Image-Consistent Attitude Refinement
Can Lei, Valerio Franchi, Hayat Rajani +3
Side-scan sonar (SSS) images are susceptible to motion-induced geometric distortion, which degrades their reliability for seabed interpretation and downstream tasks. Existing corre…
Physically Motivated Knowledge Distillation for Blind Geometric Correction of Side-Scan Sonar Imagery
Can Lei, Hayat Rajani, Valerio Franchi +4
Side-scan sonar (SSS) imagery is susceptible to geometric distortions caused by platform motion instability, which degrade geometric consistency and limit downstream analyses such…
PhysDNet: Physics-Guided Decomposition Network of Side-Scan Sonar Imagery
Can Lei, Hayat Rajani, Nuno Gracias +2
Side-scan sonar (SSS) imagery is widely used for seafloor mapping and underwater remote sensing, yet the measured intensity is strongly influenced by seabed reflectivity, terrain e…
Coarse-to-Fine Non-Rigid Registration for Side-Scan Sonar Mosaicking
Can Lei, Nuno Gracias, Rafael Garcia +2
Side-scan sonar mosaicking plays a crucial role in large-scale seabed mapping but is challenged by complex non-linear, spatially varying distortions due to diverse sonar acquisitio…
A Geometrically Consistent Matching Framework for Side-Scan Sonar Mapping
Can Lei, Hayat Rajani, Nuno Gracias +2
Robust matching of side-scan sonar imagery remains a fundamental challenge in seafloor mapping due to view-dependent backscatter, shadows, and geometric distortion. This paper prop…
SI-GAT: A method based on improved Graph Attention Network for sonar image classification
Can Lei, Huigang Wang, Juan Lei
The existing sonar image classification methods based on deep learning are often analyzed in Euclidean space, only considering the local image features. For this reason, this paper…