LRAD-Net: An Improved Lightweight Network for Building Extraction From Remote Sensing Images-Reference-Cited by-同舟云学术

LRAD-Net: An Improved Lightweight Network for Building Extraction From Remote Sensing Images

Published:2023 Issue: Volume:16 Page:675-687
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Liu Jiabin¹^ORCID,Huang Huaigang²^ORCID,Sun Hanxiao¹,Wu Zhifeng³^ORCID,Luo Renbo⁴^ORCID

Affiliation:

1. School of Geographic Science and Remote Sensing, Guangzhou University, Guangzhou, China

2. Department of Geomatics Engineering, University of Calgary, Calgary, AB, Canada

3. School of Geography and Remote Sensing, and MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Guangzhou University, Guangzhou, China

4. School of Geography and Remote Sensing, Guangzhou University, Guangzhou, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/9973430/09987671.pdf?arnumber=9987671

Reference59 articles.

1. Optimal fusion of optical and SAR high-resolution images for semiautomatic building detection

2. A robust gradient based method for building extraction from lidar and photogrammetric imagery;fasahat;SENSORS,2016

3. Pyramid scene parsing network;zhao;Proc IEEE Conf Comput Vis Pattern Recognit,2016

4. Morphological house extraction from digital surface model and imagery of high-density residential areas;yan;J Amer Soc Photogram Remote Sens,2016

Cited by 13 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. Semi-Supervised Building Extraction with Optical Flow Correction Based on Satellite Video Data in a Tsunami-Induced Disaster Scene;Sensors;2024-08-11

2. Methods and datasets on semantic segmentation for Unmanned Aerial Vehicle remote sensing images: A review;ISPRS Journal of Photogrammetry and Remote Sensing;2024-05

3. Multi-Scale Attention Network for Building Extraction from High-Resolution Remote Sensing Images;Sensors;2024-02-04

4. FADNet:Greenhouse Identification With Fusion Attention Mechanism and Deformable Convolution;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

5. MDCGA-Net: Multiscale Direction Context-Aware Network With Global Attention for Building Extraction From Remote Sensing Images;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024