A novel unsupervised deep learning method for the generalization of urban form-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A novel unsupervised deep learning method for the generalization of urban form

Published:2022-05-17 Issue:4 Volume:25 Page:568-587
ISSN:1009-5020
Container-title:Geo-spatial Information Science
language:en
Short-container-title:Geo-spatial Information Science

Author:

Cai Jihong¹^ORCID,Chen Yimin¹^ORCID

Affiliation:

1. School of Geography and Planning, Sun Yat-sen University, Guangzhou, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Guangdong Natural Science Funds for Distinguished Young Scholar

Fundamental Research Funds for the Central Universities

Publisher

Informa UK Limited

Subject

Computers in Earth Sciences,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10095020.2022.2068384

Reference71 articles.

1. Mapping and classifying green infrastructure typologies for climate-related studies based on remote sensing data

2. Urban heat island effect of a polynuclear megacity Delhi – Compactness and thermal evaluation of four sub-cities

3. Quantifying the relationships between network distance and straight-line distance: applications in spatial bias correction

4. Delineating urban functional areas with building-level social media data: A dynamic time warping (DTW) distance based k -medoids method

5. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Area extraction and growth monitoring of sugarcane from multi-source remote sensing images under a polarimetric SAR data compensation based on buildings;Geo-spatial Information Science;2024-07-30

2. A Novel Approach to Urban Village Extraction and Generalization from Digital Line Graphics Using the Computational Geometric Method and the Modified Hausdorff Distance;ISPRS International Journal of Geo-Information;2024-06-13

3. A classification framework with multi-level fusion of object-based analysis and convolutional neural network: a case study for land use classification in mining areas;Geo-spatial Information Science;2024-04-25

4. An MIU-based deep embedded clustering model for urban functional zoning from remote sensing images and VGI data;International Journal of Applied Earth Observation and Geoinformation;2024-04

5. Learning visual features from figure-ground maps for urban morphology discovery;Computers, Environment and Urban Systems;2024-04

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3