Building Extraction From LiDAR Data Applying Deep Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Building Extraction From LiDAR Data Applying Deep Convolutional Neural Networks

Published:2019-01 Issue:1 Volume:16 Page:155-159
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Maltezos Evangelos^ORCID,Doulamis Anastasios,Doulamis Nikolaos^ORCID,Ioannidis Charalabos^ORCID

Funder

EU H2020 Project TERPSICHORE “Transforming Intangible Folkloric Performing Arts into Tangible Choreographic Digital Objects”

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/8591978/08465968.pdf?arnumber=8465968

Cited by 72 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. Building Footprint Extraction from Remote Sensing Images with Residual Attention Multi-Scale Aggregation Fully Convolutional Network;Journal of the Indian Society of Remote Sensing;2024-07-31

2. Automatic Building Extraction from Multispectral LiDAR Using Novel 3D Spatial Indices and Deep Learning Point CNN;Journal of the Indian Society of Remote Sensing;2024-07-16

3. Low-cost and scalable detection of sparse informal settlements using machine learning in Gcuwa, Eastern Cape, South Africa;African Geographical Review;2024-07-08

4. Automatic building footprint extraction from photogrammetric and LiDAR point clouds using a novel improved-Octree approach;Journal of Building Engineering;2024-04

5. Smart edge segmentation and localization method for building detection in satellite imagery;Journal of Intelligent & Fuzzy Systems;2024-03-30

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