Yilang Shen
Biographic Data
| ID | 6746796 |
|---|---|
| NAME | Yilang Shen |
| GIVEN NAMES | Yilang |
| FAMILY NAME | Shen |
| SIGNATURE | SHEN Y |
| AFFILIATIONS | Sun Yat-sen University |
| ORCID | 0000-0002-9699-8551 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 2 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 1 |
Inconsistency Detection in Cross-Layer Tile Maps with Super-Pixel Segmentation
The consistency of geospatial data is of great significance for the application and updating of geographic information in web maps. Due to the multiple data sources and different temporal versions, the tile web maps usually meet the inconsistency question across different layers. This study tries to develop a method to detect this kind of inconsistency utilizing a raster-based scaling approach. Compared with vector-based handling, this method can…
A Heuristic Approach for Resolving Spatial Conflicts of Buildings in Urban Villages
Building displacement is a common operation to resolve the spatial conflicts between map features, and it has important theoretical value and practical application significance for multi-scale mapping. The prerequisite for a successful displacement operation is that there is extra space around the conflicting buildings into which they can be displaced. Otherwise, additional generalization operators need to be combined to resolve spatial conflicts…
Variable-Scale Visualization of High-Density Polygonal Buildings on a Tile Map
To better satisfy user’s needs for the accurate visualization of massive amounts of geographic data, the variable-scale expression of map content based on multilevel data organization has attracted increasing attention. Traditional methods based on vector data usually cannot handle tile data in the form of a grid on the network. Therefore, this paper proposes a variable-scale visualization method for high-density buildings based on a raster tile …
Recognition of building group patterns using graph convolutional network
Recognition of building group patterns is of great significance for understanding and modeling the urban space. However, many current methods cannot fully utilize spatial information and have trouble efficiently dealing with topographic data with high complexity. The design of intelligent computational models that can act directly on topographic data to extract spatial features is critical. To this end, we propose a novel deep neural network base…
Recognition of building group patterns using graph convolutional network
Recognition of building group patterns is of great significance for understanding and modeling the urban space. However, many current methods cannot fully utilize spatial information and have trouble efficiently dealing with topographic data with high complexity. The design of intelligent computational models that can act directly on topographic data to extract spatial features is critical. To this end, we propose a novel deep neural network base…
Recognition of building group patterns using graph convolutional network
Recognition of building group patterns is of great significance for understanding and modeling the urban space. However, many current methods cannot fully utilize spatial information and have trouble efficiently dealing with topographic data with high complexity. The design of intelligent computational models that can act directly on topographic data to extract spatial features is critical. To this end, we propose a novel deep neural network base…
Variable-Scale Visualization of High-Density Polygonal Buildings on a Tile Map
To better satisfy user’s needs for the accurate visualization of massive amounts of geographic data, the variable-scale expression of map content based on multilevel data organization has attracted increasing attention. Traditional methods based on vector data usually cannot handle tile data in the form of a grid on the network. Therefore, this paper proposes a variable-scale visualization method for high-density buildings based on a raster tile …
Inconsistency Detection in Cross-Layer Tile Maps with Super-Pixel Segmentation
The consistency of geospatial data is of great significance for the application and updating of geographic information in web maps. Due to the multiple data sources and different temporal versions, the tile web maps usually meet the inconsistency question across different layers. This study tries to develop a method to detect this kind of inconsistency utilizing a raster-based scaling approach. Compared with vector-based handling, this method can…
A Heuristic Approach for Resolving Spatial Conflicts of Buildings in Urban Villages
Building displacement is a common operation to resolve the spatial conflicts between map features, and it has important theoretical value and practical application significance for multi-scale mapping. The prerequisite for a successful displacement operation is that there is extra space around the conflicting buildings into which they can be displaced. Otherwise, additional generalization operators need to be combined to resolve spatial conflicts…
Artificial Intelligence (4 works) · Computer Science (4 works) · Data mining (4 works) · Geographic Information Systems Studies (4 works) · Geography (4 works) · Cartography (3 works) · Mathematics (3 works) · Automated Road and Building Extraction (2 works) · Data Management and Algorithms (2 works) · Raster data (2 works)