Robust multi-model fitting via neighborhood graph structure consistency
Robust multi-model fitting via neighborhood graph structure consistency is a scholarly work, published in 2024 in ''Digital Signal Processing''. The main subjects of the publication include anomaly detection, outlier, deep learning, graph, clustering coefficient, Pavement management, computer science, node, theoretical computer science, cluster analysis, and algorithm. The authors propose a novel multi-model fitting method based on neighborhood graph structure consistency (NGSC), which preserves the local neighborhood structures of potential inliers to construct an effective graph for robust model fitting.