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FL-MEC: FEDERATED LEARNING FOR NETWORK TRAFFIC CLASSIFICATION ON THE NETWORK EDGE
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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_ | 1864030189949812736 |
|---|---|
| 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:5049 |
| institution | FRELIP |
| journal_source_facet | Computer Science |
| publishDate | 2025 |
| publishDateSort | 2025 |
| record_format | rss_article |
| spellingShingle | FL-MEC: FEDERATED LEARNING FOR NETWORK TRAFFIC CLASSIFICATION ON THE NETWORK EDGE 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 | FL-MEC: FEDERATED LEARNING FOR NETWORK TRAFFIC CLASSIFICATION ON THE NETWORK EDGE |
| title_auth | FL-MEC: FEDERATED LEARNING FOR NETWORK TRAFFIC CLASSIFICATION ON THE NETWORK EDGE |
| title_full | FL-MEC: FEDERATED LEARNING FOR NETWORK TRAFFIC CLASSIFICATION ON THE NETWORK EDGE |
| title_fullStr | FL-MEC: FEDERATED LEARNING FOR NETWORK TRAFFIC CLASSIFICATION ON THE NETWORK EDGE |
| title_full_unstemmed | FL-MEC: FEDERATED LEARNING FOR NETWORK TRAFFIC CLASSIFICATION ON THE NETWORK EDGE |
| title_short | FL-MEC: FEDERATED LEARNING FOR NETWORK TRAFFIC CLASSIFICATION ON THE NETWORK EDGE |
| title_sort | fl-mec: federated learning for network traffic classification on the network edge |
| topic | Computer Science & Information Science Computer Science & IT Engineering & Technology |
| url | https://journals.agh.edu.pl/csci/article/view/7196 |