Cloud detection and classification with artificial intelligence for satellite optical image
Cloud is a very common weather phenomenon in the world. For optical satellite imaging, it is very often that more than 50% of imaging areas are covered by clouds. It sounds easy but practically very challenging to detect clouds accurately without confusing the detection with white ground, including...
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2020
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sg-ntu-dr.10356-1410432023-07-04T16:31:09Z Cloud detection and classification with artificial intelligence for satellite optical image Yao, Yuhan LU Yilong School of Electrical and Electronic Engineering EYLU@ntu.edu.sg Engineering::Electrical and electronic engineering Cloud is a very common weather phenomenon in the world. For optical satellite imaging, it is very often that more than 50% of imaging areas are covered by clouds. It sounds easy but practically very challenging to detect clouds accurately without confusing the detection with white ground, including areas covered snow or ice. This project is to study and test innovative approaches for accurate detection and classification of clouds by applying machine intelligence and big data. The project scope includes the study of image processing fundamentals, literature review of machine intelligence and cloud detection, implementation of the proposed approach, collection of cloud and snow samples, test the implemented code and detailed analysis of the results, evaluation of the detection accuracy. Master of Science (Signal Processing) 2020-06-03T08:43:06Z 2020-06-03T08:43:06Z 2020 Thesis-Master by Coursework https://hdl.handle.net/10356/141043 en application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Yao, Yuhan Cloud detection and classification with artificial intelligence for satellite optical image |
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Cloud is a very common weather phenomenon in the world. For optical satellite imaging, it is very often that more than 50% of imaging areas are covered by clouds. It sounds easy but practically very challenging to detect clouds accurately without confusing the detection with white ground, including areas covered snow or ice.
This project is to study and test innovative approaches for accurate detection and classification of clouds by applying machine intelligence and big data. The project scope includes the study of image processing fundamentals, literature review of machine intelligence and cloud detection, implementation of the proposed approach, collection of cloud and snow samples, test the implemented code and detailed analysis of the results, evaluation of the detection accuracy. |
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LU Yilong |
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LU Yilong Yao, Yuhan |
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Thesis-Master by Coursework |
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Yao, Yuhan |
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Yao, Yuhan |
title |
Cloud detection and classification with artificial intelligence for satellite optical image |
title_short |
Cloud detection and classification with artificial intelligence for satellite optical image |
title_full |
Cloud detection and classification with artificial intelligence for satellite optical image |
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Cloud detection and classification with artificial intelligence for satellite optical image |
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Cloud detection and classification with artificial intelligence for satellite optical image |
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cloud detection and classification with artificial intelligence for satellite optical image |
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Nanyang Technological University |
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2020 |
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https://hdl.handle.net/10356/141043 |
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