Fine-Grained Binary Object Segmentation in Remote Sensing Imagery via Path-Selective Test-Time Adaptation-Reference-Cited by-同舟云学术

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Fine-Grained Binary Object Segmentation in Remote Sensing Imagery via Path-Selective Test-Time Adaptation

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:

Lee Kyungsu¹^ORCID,Lee Haeyun²^ORCID,Park Juhum³^ORCID,Hwang Jae Youn⁴^ORCID

Affiliation:

1. Department of Computer Science & Artificial Intelligence, Jeonbuk National University, Jeonju, South Korea

2. School of Computer Science and Engineering, Korea University of Technology & Education, Cheonan, South Korea

3. Dabeeo Inc., Seoul, South Korea

4. Department of Electrical Engineering and Computer Science, The Interdisciplinary Studies of Artificial Intelligence, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea

Funder

Korea Research Institute for Defense Technology Planning and Advancement (KRIT) through the Korea Government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10476498.pdf?arnumber=10476498

Reference42 articles.

1. Measuring phenological variability from satellite imagery

2. A Survey of Mobile Indoor Navigation Systems

3. Microsoft COCO: Common Objects in Context

4. Deep learning for detecting robotic grasps

5. Scene Parsing through ADE20K Dataset

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