A Deep Learning Approach for Satellite and Debris Detection: YOLO in Action-Reference-Cited by-同舟云学术

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A Deep Learning Approach for Satellite and Debris Detection: YOLO in Action

Published:2023-12-13 Issue: Volume:7 Page:1-6
ISSN:
Container-title:2023 26th International Conference on Computer and Information Technology (ICCIT)
language:
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Author:

Ahamed Md Younus¹,Bin Syed Md Asif²,Chatterjee Paroma¹,Bin Habib Al Zadid Sultan¹

Affiliation:

1. West Virginia University,Lane Department of Computer Science and Electrical Engineering,Morgantown,USA,WV 26506

2. West Virginia University,Department of Industrial and Management Systems Engineering,Morgantown,USA,WV 26506

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10440723/10440967/10441152.pdf?arnumber=10441152

Reference18 articles.

1. Remotely sensed debris thickness mapping of Bara Shigri Glacier, Indian Himalaya

2. Deep learning

3. DeepGlobe 2018: A Challenge to Parse the Earth through Satellite Images

4. Revealing influencing factors on global waste distribution via deep-learning based dumpsite detection from satellite imagery

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1. Deep Learning Methods of Satellite Image Processing for Monitoring of Flood Dynamics in the Ganges Delta, Bangladesh;Water;2024-04-17

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