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This dataverse hosts the data for the NRF funded project Fully automatic CityGML-compliant city model derivation on demand.
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1 to 3 of 3 Results
Aug 12, 2020
Erdt, Marius; Zhang, Xingzi; Johan, Henry, 2020, "Source code to generate LoD1 CityGML models from city area maps",, DR-NTU (Data), V2, UNF:6:zN4RTInDz93o+Dgg2Xk9oA== [fileUNF]
Application source code to generate level of detail 1 models in CityGML format from an input image. In particular, the image has to be a city area map showing ground plans of buildings.
Aug 11, 2020
Erdt, Marius; Zhang, Xingzi; Johan, Henry, 2020, "Source code and sample input CityGML models for automatic derivation of lower levels of detail",, DR-NTU (Data), V1
This dataset contains the source code for automatically creating lower levels of detail from a given CityGML building model. E.g. a level of detail 3 model can be reduced to level of detail 0, 1, or 2. Exemplary sample models are included as well.
Aug 11, 2020
Erdt, Marius; Zhang, Xingzi; Johan, Henry, 2020, "Source code to generate a training dataset for text recognition of Singapore's city area names and block numbers",, DR-NTU (Data), V1
Source code for training a deep learning model to recognise hand written text in an image. In particular, the model recognises Singapore's city area names as well as HDB block numbers.
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