RBP-MTL: Agricultural Parcel Vectorization via Region-Boundary-Parcel Decoupled Multitask Learning-Reference-Cited by-同舟云学术

RBP-MTL: Agricultural Parcel Vectorization via Region-Boundary-Parcel Decoupled Multitask Learning

Published:2024 Issue: Volume:62 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Pan Yang¹^ORCID,Wang Xinyu²^ORCID,Wang Yu³,Zhong Yanfei¹^ORCID

Affiliation:

1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

2. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

3. Satellite Application Center for Ecology and Environment and the State Environmental Protection Key Laboratory of Satellite Remote Sensing, Ministry of Ecology and Environment, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS) Special Research Funding

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10440354.pdf?arnumber=10440354

Reference46 articles.

1. Temporal-Spatial Analysis of the Warming Effect of Different Cultivated Land Urbanization of Metropolitan Area in China

2. The land parcel identification system: A useful tool to determine the eligibility of agricultural land—But its management could be further improved;Owen,2016

3. Detection of cropland field parcels from Landsat imagery

4. Edge- and region-based segmentation technique for the extraction of large, man-made objects in high-resolution satellite imagery

5. Field-based sub-boundary extraction from remote sensing imagery using perceptual grouping

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