Detecting Corresponding Vertex Pairs between Planar Tessellation Datasets with Agglomerative Hierarchical Cell-Set Matching
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Summary
The proposed method was applied to complicated synthetic cell datasets assumed as a cadastral map and a topographical map and showed an improved result with the F-measures, regardless of locally uneven positional discrepancies between dataset.
- Type
- dissertation
- Published
- 2016-06-27
- Cited by
- 0
- References
- 25
- Access
- Open access
- OpenAlex
- https://openalex.org/W27348229
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:18057390
Keywords
Curriculum, Nursing, Medical education, Medicine, Professional development
References
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- Matching spatial data sets: a statistical approach
- A Method for Registration of 3-D Shapes
- Extended Hausdorff distance for spatial objects in GIS
- Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
- Feature correspondence and deformable object matching via agglomerative correspondence clustering
- Bipartite isoperimetric graph partitioning for data co-clustering
- Background and threshold: critical comparison of methods of determination.
- Co-clustering documents and words using bipartite spectral graph partitioning
- Graph Embedding and Extensions: A General Framework for Dimensionality Reduction
- Image registration methods: a survey
- Local Edge Matching for Seamless Adjacent Spatial Datasets with Sequence Alignment
- Integration of heterogeneous geospatial data in a federated database
- Multivariate Analysis
- Road map towards the implementation of the United Nations Millennium Declaration
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