Point-Based Weakly Supervised Deep Learning for Semantic Segmentation of Remote Sensing Images-Reference-Cited by-同舟云学术

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Point-Based Weakly Supervised Deep Learning for Semantic Segmentation of Remote Sensing Images

Published:2024 Issue: Volume:62 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Zhao Yuanhao¹,Sun Genyun¹^ORCID,Ling Ziyan²^ORCID,Zhang Aizhu¹^ORCID,Jia Xiuping³^ORCID

Affiliation:

1. College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, China

2. School of Information and Control Engineering, Qingdao University of Technology, Qingdao, China

3. School of Engineering and Information Technology, University of New South Wales at Canberra, Canberra, ACT, Australia

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/36/10354519/10597372.pdf?arnumber=10597372

Reference58 articles.

1. A Comparison of Deep Learning Methods for Semantic Segmentation of Coral Reef Survey Images

2. Landcover classification in MRF context using Dempster-Shafer fusion for multisensor imagery

3. Utilizing Hierarchical Segmentation to Generate Water and Snow Masks to Facilitate Monitoring Change with Remotely Sensed Image Data

4. Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes

5. Mapping urbanization dynamics at regional and global scales using multi-temporal DMSP/OLS nighttime light data

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