Guangxia Wang
Biographic Data
| ID | 6746665 |
|---|---|
| NAME | Guangxia Wang |
| GIVEN NAMES | Guangxia |
| FAMILY NAME | Wang |
| SIGNATURE | WANG G |
| AFFILIATIONS | Henan University |
| ORCID | 0000-0002-5638-4838 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
MapLayNet
Cartography and Neural Networks
Propelled by emerging technologies such as artificial intelligence and deep learning, the essence and scope of cartography have significantly expanded. The rapid progress in neuroscience has raised high expectations for related disciplines, furnishing theoretical support for revealing and deepening the essence of maps. In this study, CiteSpace was used to examine the confluence of cartography and neural networks over the past decade (2013–2023), …
Road Network Intelligent Selection Method Based on Heterogeneous Graph Attention Neural Network
Selecting road networks in cartographic generalization has consistently posed formidable challenges, driving research toward the application of intelligent models. Despite previous efforts, the accuracy and connectivity preservation in these studies, particularly when dealing with road types of similar sample sizes, still warrant improvement. To address these shortcomings, we introduce a Heterogeneous Graph Attention Network (HAN) for road select…
Simulation of wetland distribution in the Yellow River Basin based on an improved Markov-FLUS model
Wetlands, as a regulator of water cycle and balance, play a key role in preventing flood and drought disasters and protecting biodiversity. The Yellow River Basin is an important ecological barrier and economic zone in our country. By predicting the distribution of wetland landscape and evaluating its evolutionary characteristics, strategies for wetland conservation and utilization in the Yellow River Basin can be formulated. Future land use simu…
Research on the Cyberspace Map and Its Conceptual Model
The cyberspace map, as one of the important tools for describing cyberspace, provides a visual representation of the dynamic and elusive nature of cyberspace. It has become a research hotspot in multiple disciplinary fields. Compared with traditional maps, cyberspace maps lack the guidance of cartography theory and have not yet formed a unified understanding. Clarifying the concept of the cyberspace map and developing a conceptual model of it cou…
Building Block Extraction from Historical Maps Using Deep Object Attention Networks
The geographical feature extraction of historical maps is an important foundation for realizing the transition from human map reading to machine map reading. The current methods for building block extraction from historical maps have many problems, such as low accuracy and poor scalability. Moreover, the high cost of annotating historical maps further limits its applications. In this study, a method for extracting building blocks from historical …
No prominent works on this page.
Building Block Extraction from Historical Maps Using Deep Object Attention Networks
The geographical feature extraction of historical maps is an important foundation for realizing the transition from human map reading to machine map reading. The current methods for building block extraction from historical maps have many problems, such as low accuracy and poor scalability. Moreover, the high cost of annotating historical maps further limits its applications. In this study, a method for extracting building blocks from historical …
Research on the Cyberspace Map and Its Conceptual Model
The cyberspace map, as one of the important tools for describing cyberspace, provides a visual representation of the dynamic and elusive nature of cyberspace. It has become a research hotspot in multiple disciplinary fields. Compared with traditional maps, cyberspace maps lack the guidance of cartography theory and have not yet formed a unified understanding. Clarifying the concept of the cyberspace map and developing a conceptual model of it cou…
Cartography and Neural Networks
Propelled by emerging technologies such as artificial intelligence and deep learning, the essence and scope of cartography have significantly expanded. The rapid progress in neuroscience has raised high expectations for related disciplines, furnishing theoretical support for revealing and deepening the essence of maps. In this study, CiteSpace was used to examine the confluence of cartography and neural networks over the past decade (2013–2023), …
Road Network Intelligent Selection Method Based on Heterogeneous Graph Attention Neural Network
Selecting road networks in cartographic generalization has consistently posed formidable challenges, driving research toward the application of intelligent models. Despite previous efforts, the accuracy and connectivity preservation in these studies, particularly when dealing with road types of similar sample sizes, still warrant improvement. To address these shortcomings, we introduce a Heterogeneous Graph Attention Network (HAN) for road select…
Simulation of wetland distribution in the Yellow River Basin based on an improved Markov-FLUS model
Wetlands, as a regulator of water cycle and balance, play a key role in preventing flood and drought disasters and protecting biodiversity. The Yellow River Basin is an important ecological barrier and economic zone in our country. By predicting the distribution of wetland landscape and evaluating its evolutionary characteristics, strategies for wetland conservation and utilization in the Yellow River Basin can be formulated. Future land use simu…
MapLayNet
Artificial Intelligence (5 works) · Computer Science (5 works) · Artificial neural network (3 works) · Machine learning (3 works) · Advanced Image and Video Retrieval Techniques (2 works) · Data mining (2 works) · Geographic Information Systems Studies (2 works) · Geography (2 works) · Graph (2 works) · Theoretical Computer Science (2 works)