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A Skeleton-Line-Based Graph Convolutional Neural Network for Areal Settlements’ Shape Classification
5 references·1 citing·26 second hop
A Skeleton-Line-Based Graph Convolutional Neural Network for Areal Settlements’ Shape Classification (2022)A Skeleton-Line-Based Graph Convolutional…Template Matching and Simplification Method for Building Features Based on Shape Cognition (2017)Template Matching and Simplif…A Simplification of Residential Feature by the Shape Cognition and Template Matching Method (2016)A Simplification of Residenti…Analytical Estimation of Map Readability (2015)Analytical Estimation of Map …Automated evaluation of building alignments in generalized maps (2013)Automated evaluation of build…Methodology for evaluating automated map generalization in commercial software (2009)Methodology for evaluating au…Submarine Terrain Generalization in Nautical Charts: A Survey of Traditional Methods and Graph Neural Network Solutions (2025)Submarine Terrain Generalizat…Map Generalization: Making Rules for Knowledge Representation (1991)GENERALIZATION BASED ON LEAST SQUARES ADJUSTMENT (2000)Contextual Building Typification in Automated Map Generalization (2001)Evaluation in Generalisation (2014)A typification method for linear pattern in urban building generalisation (2016)Constraint-Based Evaluation of Map Images Generalized by Deep Learning (2022)GIS and Generalization: Methodology and Practice (1996)Generalisation of Geographic Information: Cartographic Modelling and Applications (2007)Fully automated generalization of a 1:50k map from 1:10k data (2013)Abstracting Geographic Information in a Data Rich World (2014)Is deep learning the new agent for map generalization? (2019)The Principles of Selection (1966)Cartographic generalization in a digital environment: when and how to generalize (1989)Generalization in Digital Cartography (1992)Clutter and Map Legibility in Automated Cartography: A Research Agenda (2016)Designing multi-scale maps: lessons learned from existing practices (2020)Label Placement Challenges in City Wayfinding Map Production—Identification and Possible Solutions (2022)Optimization approaches for generalization and data abstraction (2005)Quality assessment for building footprints data on OpenStreetMap (2014)A deep learning approach for polyline and building simplification based on graph autoencoder with flexible constraints (2023)Move and remove: Multi-task learning for building simplification in vector maps with a graph convolutional neural network (2023)Machine learning in cartography (2024)A review and conceptual framework of automated map generalization (1988)Line Generalization Based on Analysis of Shape Characteristics (1998)Quantitative Relations between Topological Similarity Degree and Map Scale Change of Contour Clusters in Multi-Scale Map Spaces (2022)A polygonal buildings aggregation method considering obstacle elements and visual clarity (2023)
this work references cited by second hop

References

  • 2009Methodology for evaluating automated map generalization in commercial software84 cited
  • 2017Template Matching and Simplification Method for Building Features Based on Shape Cognition48 cited
  • 2013Automated evaluation of building alignments in generalized maps46 cited
  • 2015Analytical Estimation of Map Readability37 cited
  • 2016A Simplification of Residential Feature by the Shape Cognition and Template Matching Method14 cited

Cited by

  • 2025Submarine Terrain Generalization in Nautical Charts: A Survey of Traditional Methods and Graph Neural Network Solutions3 cited

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