Building Extraction From High Spatial Resolution Remote Sensing Images of Complex Scenes by Combining Region-Line Feature Fusion and OCNN

Author:

Dong Dehui1ORCID,Ming Dongping1ORCID,Weng Qihao2ORCID,Yang Yi3,Fang Kun1,Xu Lu1,Du Tongyao1,Zhang Yu1,Liu Ran1

Affiliation:

1. School of Information Engineering, China University of Geosciences (Beijing), Beijing, China

2. Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong

3. Chinese Academy of Surveying and Mapping, Beijing, China

Funder

State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR, CASM

Fundamental Research Funds for the Central Universities

2023 Graduate Innovation Fund Project of China University of Geosciences, Beijing

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Reference62 articles.

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2. Dense extreme inception network: Towards a robust cnn model for edge detection;poma;Proc IEEE/CVF Winter Conf Appl Comput Vis,2020

3. Delineation of cultivated land parcels based on deep convolutional networks and geographical thematic scene division of remotely sensed images

4. Object Contour Detection with a Fully Convolutional Encoder-Decoder Network

5. Classification with an edge: Improving semantic image segmentation with boundary detection

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