HYBRID DEEP LEARNING APPROACH FOR DETECTING AND CLASSIFYING SPACE DEBRIS IN LOW EARTH ORBIT
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| Format: | masterThesis |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://eprints.kfupm.edu.sa/id/eprint/143628/1/Thesis_Report.pdf |
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| _version_ | 1864513387538415616 |
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| author | unknown |
| author_facet | unknown |
| author_role | author |
| dc.creator.*.fl_str_mv | unknown |
| dc.date.*.fl_str_mv | 2020 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/143628/1/Thesis_Report.pdf HYBRID DEEP LEARNING APPROACH FOR DETECTING AND CLASSIFYING SPACE DEBRIS IN LOW EARTH ORBIT. Masters thesis, King Fahd University of Petroleum and Minerals. |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/143628/ |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Research Engineering Aerospace |
| dc.title.none.fl_str_mv | HYBRID DEEP LEARNING APPROACH FOR DETECTING AND CLASSIFYING SPACE DEBRIS IN LOW EARTH ORBIT |
| dc.type.none.fl_str_mv | Thesis NonPeerReviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/masterThesis |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| id | KFUPM_1e9ba3e94c2614a96ac8dd1fede5fd28 |
| identifier_str_mv | HYBRID DEEP LEARNING APPROACH FOR DETECTING AND CLASSIFYING SPACE DEBRIS IN LOW EARTH ORBIT. Masters thesis, King Fahd University of Petroleum and Minerals. |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai::143628 |
| publishDate | 2020 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | HYBRID DEEP LEARNING APPROACH FOR DETECTING AND CLASSIFYING SPACE DEBRIS IN LOW EARTH ORBITResearchEngineeringAerospaceThesisNonPeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/143628/1/Thesis_Report.pdf HYBRID DEEP LEARNING APPROACH FOR DETECTING AND CLASSIFYING SPACE DEBRIS IN LOW EARTH ORBIT. Masters thesis, King Fahd University of Petroleum and Minerals. enhttps://eprints.kfupm.edu.sa/id/eprint/143628/2020info:eu-repo/semantics/openAccessunknownoai::1436282025-07-31T07:56:09Z |
| spellingShingle | HYBRID DEEP LEARNING APPROACH FOR DETECTING AND CLASSIFYING SPACE DEBRIS IN LOW EARTH ORBIT unknown Research Engineering Aerospace |
| status_str | publishedVersion |
| title | HYBRID DEEP LEARNING APPROACH FOR DETECTING AND CLASSIFYING SPACE DEBRIS IN LOW EARTH ORBIT |
| title_full | HYBRID DEEP LEARNING APPROACH FOR DETECTING AND CLASSIFYING SPACE DEBRIS IN LOW EARTH ORBIT |
| title_fullStr | HYBRID DEEP LEARNING APPROACH FOR DETECTING AND CLASSIFYING SPACE DEBRIS IN LOW EARTH ORBIT |
| title_full_unstemmed | HYBRID DEEP LEARNING APPROACH FOR DETECTING AND CLASSIFYING SPACE DEBRIS IN LOW EARTH ORBIT |
| title_short | HYBRID DEEP LEARNING APPROACH FOR DETECTING AND CLASSIFYING SPACE DEBRIS IN LOW EARTH ORBIT |
| title_sort | HYBRID DEEP LEARNING APPROACH FOR DETECTING AND CLASSIFYING SPACE DEBRIS IN LOW EARTH ORBIT |
| topic | Research Engineering Aerospace |
| url | https://eprints.kfupm.edu.sa/id/eprint/143628/1/Thesis_Report.pdf |