data_code.zip

this study proposes a novel Multimodal Historical Street Identification Network (MHSI-Net) that integrates street-related semantics to identify streets from specific construction periods in historical maps. It comprises three primary modules: multimodal representation learning, multimodal interactive fusion, and an interpretable attention-enhanced method. These modules are designed to extract features of street morphology from street images and network structure from street graph, facilitate cross-scale semantic fusion and capture local-global connections, and ultimately improve identification accuracy and interpretability.