• Produktbild: Spatial Data and Intelligence
  • Produktbild: Spatial Data and Intelligence
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Spatial Data and Intelligence 5th China Conference, SpatialDI 2024, Nanjing, China, April 25–27, 2024, Proceedings

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.05.2024

Abbildungen

XIII, 358 p. 151 illus., 136 illus. in color.

Herausgeber

Xiaofeng Meng + weitere

Verlag

Springer Singapore

Seitenzahl

358

Maße (L/B/H)

23,5/15,5/2,1 cm

Gewicht

563 g

Auflage

2024

Sprache

Englisch

ISBN

978-981-9729-65-4

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.05.2024

Abbildungen

XIII, 358 p. 151 illus., 136 illus. in color.

Herausgeber

Verlag

Springer Singapore

Seitenzahl

358

Maße (L/B/H)

23,5/15,5/2,1 cm

Gewicht

563 g

Auflage

2024

Sprache

Englisch

ISBN

978-981-9729-65-4

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Spatial Data and Intelligence
  • Produktbild: Spatial Data and Intelligence

  • .-
    Spatiotemporal Data Analysis
    .  


    .- Multi-view Contrastive Clustering with Clustering Guidance and Adaptive Auto-en-coders.  


    .- Cloud-Edge Collaborative Continual Adaptation for ITS Object Detection.  


    .- Understanding Spatial Dependency among Spatial Interactions.  


    .- An Improved DBSCAN Clustering Method for AIS Trajectories Incorporating DP Compression and Discrete Fréchet Distance.  


    .- Structure and Semantic Contrastive Learning for Nodes Clustering in Heterogeneous Information Networks.  


    .- Accuracy Evaluation Method for Vector Data Based on Hexagonal Discrete Global Grid.  


    .- Applying Segment Anything Model to Ground-Based Video Surveillance for Identify-ing Aquatic Plant.  


    .-
    Spatiotemporal Data Mining
    .  


    .- Mining Regional High Utility Co-location Pattern.  


    .- Local Co-location Pattern Mining Based on Regional Embedding.  


    .- RCPM_RLM: A Regional Co-location Pattern Mining Method Based on Representa-tion Learning Model.  


    .- Construction of a Large-Scale Maritime Elements Semantic Schema Based on Hetero-geneous Graph Models.  


    .- OCGATL: One-Class Graph Attention Networks with Transformation Learning for Anomaly Detection For Argo Data.  


    .- RGCNdist2vec: Using Graph Convolutional Networks and Distance2Vector to Esti-mate Shortest Path Distance along Road Networks.  


    .- Self-supervised Graph Neural Network based Community Search over Heterogeneous Information Networks.  


    .- Measurement and Research on the Conflict between Residential Space and Tourism Space in Pianyan Ancient Township.  


    .-
    Spatiotemporal Data Prediction
    .  


    .- Spatio-Temporal Sequence Prediction Of Diversion Tunnel Based On Machine Learn-ing Multivariate Data Fusion.  


    .- DyAdapTransformer: Dynamic Adaptive Spatial-Temporal Graph Transformer for Traffic Prediction.  


    .- Predicting Future Spatio-Temporal States Using a Robust Causal Graph Attention Model.  


    .-
    Remote Sensing Data Classification
    .  


    .- MADB-RemdNet for Few-Shot Learning in Remote Sensing Classification.  


    .- Convolutional Neural Network Based on Multiple Attention Mechanisms for Hyper-spectral and LiDAR Classification.  


    .- Few-shot Learning Remote Scene Classification Based On DC-2DEC.  


    .-
    Applications of Spatiotemporal Data Mining
    .  


    .- Neural HD Map Generation from Multiple Vectorized Tiles Locally Produced by Au-tonomous Vehicles.  


    .- Trajectory Data Semi-fragile Watermarking Algorithm Considering Spatiotemporal Features.  


    .- HPO-LGBM-DRI: Dynamic Recognition Interval Estimation for Imbalanced Fraud Call via HPO-LGBM.  


    .- A Review on Urban Modelling for Future Smart Cities.