Bowei Wen
Biographic Data
| ID | 9966065 |
|---|---|
| NAME | Bowei Wen |
| GIVEN NAMES | Bowei |
| FAMILY NAME | Wen |
| SIGNATURE | WEN B |
| AFFILIATIONS | PLA Information Engineering University |
| VERIFIED | No |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Leveraging Deep Convolutional Neural Network for Point Symbol Recognition in Scanned Topographic Maps
Point symbols on a scanned topographic map (STM) provide crucial geographic information. However, point symbol recognition entails high complexity and uncertainty owing to the stickiness of map elements and singularity of symbol structures. Therefore, extracting point symbols from STMs is challenging. Currently, point symbol recognition is performed primarily through pattern recognition methods that have low accuracy and efficiency. To address th…
Progressive Collapse of Dual-Line Rivers Based on River Segmentation Considering Cartographic Generalization Rules
Collapse is a common cartographic generalization operation in multi-scale representation and cascade updating of vector spatial data. During transformation from large- to small-scale, the dual-line river shows progressive collapse from narrow river segment to line. The demand for vector spatial data with various scales is increasing; however, research on the progressive collapse of dual-line rivers is lacking. Therefore, we proposed a progressive…
A Multi-Scale Residential Areas Matching Method Considering Spatial Neighborhood Features
Residential areas is one of the basic geographical elements on the map and an important content of the map representation. Multi-scale residential areas matching refers to the process of identifying and associating entities with the same name in different data sources, which can be widely used in map compilation, data fusion, change detection and update. A matching method considering spatial neighborhood features is proposed to solve the complex …
Generation Method for Shaded Relief Based on Conditional Generative Adversarial Nets
Relief shading is the primary method for effectively representing three-dimensional terrain on a two-dimensional plane. Despite its expressiveness, manual relief shading is difficult and time-consuming. In contrast, although analytical relief shading is fast and efficient, the visual effect is quite different from that of manual relief shading due to the low degree of terrain generalisation, inability to adjust local illumination, and difficulty …
No prominent works on this page.
Progressive Collapse of Dual-Line Rivers Based on River Segmentation Considering Cartographic Generalization Rules
Collapse is a common cartographic generalization operation in multi-scale representation and cascade updating of vector spatial data. During transformation from large- to small-scale, the dual-line river shows progressive collapse from narrow river segment to line. The demand for vector spatial data with various scales is increasing; however, research on the progressive collapse of dual-line rivers is lacking. Therefore, we proposed a progressive…
A Multi-Scale Residential Areas Matching Method Considering Spatial Neighborhood Features
Residential areas is one of the basic geographical elements on the map and an important content of the map representation. Multi-scale residential areas matching refers to the process of identifying and associating entities with the same name in different data sources, which can be widely used in map compilation, data fusion, change detection and update. A matching method considering spatial neighborhood features is proposed to solve the complex …
Generation Method for Shaded Relief Based on Conditional Generative Adversarial Nets
Relief shading is the primary method for effectively representing three-dimensional terrain on a two-dimensional plane. Despite its expressiveness, manual relief shading is difficult and time-consuming. In contrast, although analytical relief shading is fast and efficient, the visual effect is quite different from that of manual relief shading due to the low degree of terrain generalisation, inability to adjust local illumination, and difficulty …
Leveraging Deep Convolutional Neural Network for Point Symbol Recognition in Scanned Topographic Maps
Point symbols on a scanned topographic map (STM) provide crucial geographic information. However, point symbol recognition entails high complexity and uncertainty owing to the stickiness of map elements and singularity of symbol structures. Therefore, extracting point symbols from STMs is challenging. Currently, point symbol recognition is performed primarily through pattern recognition methods that have low accuracy and efficiency. To address th…
Artificial Intelligence (4 works) · Computer Science (4 works) · Cartography (3 works) · Geography (3 works) · Mathematics (3 works) · Automated Road and Building Extraction (2 works) · Geographic Information Systems Studies (2 works) · Remote Sensing and LiDAR Applications (2 works) · 3D Shape Modeling and Analysis (1 works) · 3D Surveying and Cultural Heritage (1 works)