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RECONSTRUCTION OF MUON BUNDLES IN KM3NET DETECTORS USING MACHINE LEARNING METHODS
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| Published in: | Computer Science |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2025
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| Subjects: | |
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| _version_ | 1864030189112000517 |
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| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Computer Science |
| description | |
| discipline_display | Engineering & Technology |
| discipline_facet | Engineering & Technology |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:5055 |
| institution | FRELIP |
| journal_source_facet | Computer Science |
| publishDate | 2025 |
| publishDateSort | 2025 |
| record_format | rss_article |
| spellingShingle | RECONSTRUCTION OF MUON BUNDLES IN KM3NET DETECTORS USING MACHINE LEARNING METHODS Computer Science & Information Science Computer Science & IT Engineering & Technology |
| sub_discipline_display | Computer Science & IT |
| sub_discipline_facet | Computer Science & IT |
| subject_display | Computer Science & Information Science Computer Science & IT Engineering & Technology Computer Science & Information Science Computer Science & IT Engineering & Technology |
| subject_facet | Computer Science & Information Science Computer Science & IT Engineering & Technology |
| title | RECONSTRUCTION OF MUON BUNDLES IN KM3NET DETECTORS USING MACHINE LEARNING METHODS |
| title_auth | RECONSTRUCTION OF MUON BUNDLES IN KM3NET DETECTORS USING MACHINE LEARNING METHODS |
| title_full | RECONSTRUCTION OF MUON BUNDLES IN KM3NET DETECTORS USING MACHINE LEARNING METHODS |
| title_fullStr | RECONSTRUCTION OF MUON BUNDLES IN KM3NET DETECTORS USING MACHINE LEARNING METHODS |
| title_full_unstemmed | RECONSTRUCTION OF MUON BUNDLES IN KM3NET DETECTORS USING MACHINE LEARNING METHODS |
| title_short | RECONSTRUCTION OF MUON BUNDLES IN KM3NET DETECTORS USING MACHINE LEARNING METHODS |
| title_sort | reconstruction of muon bundles in km3net detectors using machine learning methods |
| topic | Computer Science & Information Science Computer Science & IT Engineering & Technology |
| url | https://journals.agh.edu.pl/csci/article/view/7062 |