Similarity based city data transfer framework in urban digitization
Abstract Cross-city transfer learning aims to apply the knowledge and model from data-rich cities to data-poor cities to solve the cold start problem.Existing methods directly transfer the model constructed from developed cities to underdeveloped cities without considering the similarity between them, which leads to a potential transfer mismatch pr