Addressing Fine-Grained Lake Water Body Extraction: A Hybrid Approach Combining Vision Transformer and Geodesic Active Contour-Reference-Cited by-同舟云学术

Addressing Fine-Grained Lake Water Body Extraction: A Hybrid Approach Combining Vision Transformer and Geodesic Active Contour

Published:2024 Issue: Volume:62 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Qi Haochen¹^ORCID,Kong Xiangwei¹^ORCID,Cheng Liu¹^ORCID,Hu Jiexin²,Gu Jianyi¹^ORCID

Affiliation:

1. School of Mechanical Engineering and Automation and the Key Laboratory of Vibration and Control of Aero-Propulsion Systems, Ministry of Education of China, Northeastern University, Shenyang, China

2. Institute of Comprehensive Technology and Economic Research, China State Shipbuilding Corporation, Beijing, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

State Ministry of Science and Technology Innovation Fund of China

National Natural Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10476619.pdf?arnumber=10476619

Reference48 articles.

1. A new active contour remote sensing river image segmentation algorithm inspired from the cross entropy

2. WSF-NET: Weakly Supervised Feature-Fusion Network for Binary Segmentation in Remote Sensing Image

3. Critical review on deep learning methodologies employed for water-body segmentation through remote sensing images

4. Semantic segmentation of water bodies in very high-resolution satellite and aerial images

5. DensePPMUNet-a: A Robust Deep Learning Network for Segmenting Water Bodies From Aerial Images

Cited by 1 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. QTU-Net: Quaternion Transformer-Based U-Net for Water Body Extraction of RGB Satellite Image;IEEE Transactions on Geoscience and Remote Sensing;2024