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Quanlong Feng

Biographic Data

ID4417445
NAMEQuanlong Feng
GIVEN NAMESQuanlong
FAMILY NAMEFeng
SIGNATUREFENG Q
AFFILIATIONSChina Agricultural University
ORCID0000-0002-0569-4131
VERIFIEDYes
TOTAL WORKS2
TOTAL CITATIONS0
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2020
LATEST PUBLICATION YEAR2024
H-INDEX0
  • Mapping urban villages based on point-of-interest data and a deep learning approach

    Open Access•Ting Li, Quanlong Feng et al.•ARTICLE•Cities•2024

  • Urban Green Plastic Cover Mapping Based on VHR Remote Sensing Images and a Deep Semi-Supervised Learning Framework

    Open Access•Jiantao Liu, Quanlong Feng et al.•ARTICLE•ISPRS International Journal of…•2020

    With the rapid process of both urban sprawl and urban renewal, large numbers of old buildings have been demolished in China, leading to wide spread construction sites, which could cause severe dust contamination. To alleviate the accompanied dust pollution, green plastic mulch has been widely used by local governments of China. Therefore, timely and accurate mapping of urban green plastic covered regions is of great significance to both urban env…

No prominent works on this page.

  • Urban Green Plastic Cover Mapping Based on VHR Remote Sensing Images and a Deep Semi-Supervised Learning Framework

    Open Access•Jiantao Liu, Quanlong Feng et al.•ARTICLE•ISPRS International Journal of…•2020

    With the rapid process of both urban sprawl and urban renewal, large numbers of old buildings have been demolished in China, leading to wide spread construction sites, which could cause severe dust contamination. To alleviate the accompanied dust pollution, green plastic mulch has been widely used by local governments of China. Therefore, timely and accurate mapping of urban green plastic covered regions is of great significance to both urban env…

  • Mapping urban villages based on point-of-interest data and a deep learning approach

    Open Access•Ting Li, Quanlong Feng et al.•ARTICLE•Cities•2024

Artificial Intelligence (2 works) · Computer Science (2 works) · Deep learning (2 works) · Geography (2 works) · Land Use and Ecosystem Services (2 works) · Automated Road and Building Extraction (1 work) · Cartography (1 work) · Civil engineering (1 work) · Convolutional neural network (1 work) · Data science (1 work)

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