Explicit Incorporation of Spatial Autocorrelation in 3D Deep Learning for Geospatial Object Detection-Reference-Cited by-同舟云学术

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Explicit Incorporation of Spatial Autocorrelation in 3D Deep Learning for Geospatial Object Detection

Published:2024-08-14 Issue: Volume: Page:1-20
ISSN:2469-4452
Container-title:Annals of the American Association of Geographers
language:en
Short-container-title:Annals of the American Association of Geographers

Author:

Chen Tianyang¹^ORCID,Tang Wenwu¹²,Allan Craig¹,Chen Shen-En³

Affiliation:

1. Department of Earth, Environmental, and Geographical Sciences, and Center for Applied GIScience, University of North Carolina at Charlotte, USA

2. School of Data Science, University of North Carolina at Charlotte, USA

3. Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, USA

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/24694452.2024.2380898

Reference54 articles.

1. 3D Semantic Parsing of Large-Scale Indoor Spaces

2. Geostatistical classification for remote sensing: an introduction

3. Incorporating Multiple Index Vectors and Feedback to Improve Urban Objects Retrieval

4. A Spatial Dependence Approach to Retrieving Industrial Complexes from Digital Images

5. ConvPoint: Continuous convolutions for point cloud processing

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