Region adjacency graph based GNN approach for static signature classification
Region adjacency graph based GNN approach for static signature classification is a scholarly work, published in 2024 in ''Journal of Intelligent and Fuzzy Systems''. The main subjects of the publication include Multi-label classification, graph, artificial intelligence, signature, graph neural network, pattern recognition, adjacency list, and computer science. Experimental results on genuine and counterfeit signature networks demonstrate that the authors' computed model enables a high rate of accuracy (GPDSsynthetic 99.91% and MCYT-75 99.56%) and minimum range of loss (GPDSsynthetic 0.0061 and MCYT-75 0.0070) on node classification..