Work

CartoMark: a benchmark dataset for map pattern recognition and map content retrieval with machine intelligence

Year: 2024

Type: data-paper

Abstract: Maps are fundamental medium to visualize and represent the real word in a simple and philosophical way. The emergence of the big data tide has made a proportion of maps generated from multiple sources, significantly enriching the dimensions and perspectives for understanding the characteristics of the real world. However, a majority of these map datasets remain undiscovered, unacquired and ineffectively used, which arises from the lack of numerous well-labelled benchmark datasets, which are of significance to implement the deep learning techniques into identifying complicated map content. To address this issue, we develop a large-scale benchmark dataset involving well-labelled datasets to employ the state-of-the-art machine intelligence technologies for map text annotation recognition, map scene classification, map super-resolution reconstruction, and map style transferring. Furthermore, these well-labelled datasets would facilitate map feature detection, map pattern recognition and map content retrieval. We hope our efforts would provide well-labelled data resources for advancing the ability to recognize and discover valuable map content.

Source: Scientific Data

DOI: 10.1038/s41597-024-04057-7