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Edge-efficient AI for acoustic channel estimation in resource-constrained subsurface IoT systems
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| Published in: | Complex & Intelligent Systems |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
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| Subjects: | |
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| _version_ | 1868207806818025475 |
|---|---|
| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Complex & Intelligent Systems |
| description | |
| discipline_display | Computer Science |
| discipline_facet | Computer Science |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:92543 |
| institution | FRELIP |
| journal_source_facet | Complex & Intelligent Systems |
| last_indexed | 2026-06-17T02:03:19.776Z |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | Edge-efficient AI for acoustic channel estimation in resource-constrained subsurface IoT systems Computer Science General Computer Science |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Computer Science General Computer Science Computer Science General Computer Science |
| subject_facet | Computer Science General Computer Science |
| title | Edge-efficient AI for acoustic channel estimation in resource-constrained subsurface IoT systems |
| title_auth | Edge-efficient AI for acoustic channel estimation in resource-constrained subsurface IoT systems |
| title_full | Edge-efficient AI for acoustic channel estimation in resource-constrained subsurface IoT systems |
| title_fullStr | Edge-efficient AI for acoustic channel estimation in resource-constrained subsurface IoT systems |
| title_full_unstemmed | Edge-efficient AI for acoustic channel estimation in resource-constrained subsurface IoT systems |
| title_short | Edge-efficient AI for acoustic channel estimation in resource-constrained subsurface IoT systems |
| title_sort | edge-efficient ai for acoustic channel estimation in resource-constrained subsurface iot systems |
| topic | Computer Science General Computer Science |
| url | https://link.springer.com/article/10.1007/s40747-026-02355-8 |