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Found 7 papers, 2 papers with code
Towards the automated large-scale reconstruction of past road networks from historical maps
Transportation infrastructure, such as road or railroad networks, represent a fundamental component of our civilization.
Synthetic Map Generation to Provide Unlimited Training Data for Historical Map Text Detection
We show that the state-of-the-art text detection models (e. g., PSENet) can benefit from the synthetic historical maps and achieve significant improvement for historical map text detection.
Guided Generative Models using Weak Supervision for Detecting Object Spatial Arrangement in Overhead Images
Recent semi-supervised clustering approaches can reduce manual labeling but still require annotations for all object categories in the image.
A Label Correction Algorithm Using Prior Information for Automatic and Accurate Geospatial Object Recognition
Thousands of scanned historical topographic maps contain valuable information covering long periods of time, such as how the hydrography of a region has changed over time.
An Automatic Approach for Generating Rich, Linked Geo-Metadata from Historical Map Images
This paper presents an end-to-end approach to address the real-world problem of finding and indexing historical map images.
Optical Character Recognition
Optical Character Recognition (OCR)
Learning the Semantics of Structured Data Sources
This model represents the semantics of the new source in terms of the concepts and relationships defined by the domain ontology.
Constructing Reference Sets from Unstructured, Ungrammatical Text
We also compare the reference-set-based extraction approach using the machine-constructed reference set to supervised extraction approaches using generic features.
