Adversarial Domain Adaptation for Metal Cutting Sound Detection: Leveraging Abundant Lab Data for Scarce Industry Data. Mostafiz, M. I., Kim, E., Li, A. S., Bertino, E., Jun, M. B., & Shakouri, A. In INDIN, pages 1-8, 2024. IEEE. ![Adversarial Domain Adaptation for Metal Cutting Sound Detection: Leveraging Abundant Lab Data for Scarce Industry Data. [link]](https://bibbase.org/img/filetypes/link.svg "link")
Link Paper bibtex @inproceedings{conf/indin/MostafizKLBJS24,
added-at = {2025-01-16T00:00:00.000+0100},
author = {Mostafiz, Mir Imtiaz and Kim, Eunseob and Li, Adrian Shuai and Bertino, Elisa and Jun, Martin Byung-Guk and Shakouri, Ali},
biburl = {https://www.bibsonomy.org/bibtex/21dc917a04052a8313de704d8247b758d/dblp},
booktitle = {INDIN},
crossref = {conf/indin/2024},
ee = {https://doi.org/10.1109/INDIN58382.2024.10774310},
interhash = {d11eca9b88529213685ed2959ce861c1},
intrahash = {1dc917a04052a8313de704d8247b758d},
isbn = {979-8-3315-2747-1},
keywords = {dblp},
pages = {1-8},
publisher = {IEEE},
timestamp = {2025-01-20T07:28:09.000+0100},
title = {Adversarial Domain Adaptation for Metal Cutting Sound Detection: Leveraging Abundant Lab Data for Scarce Industry Data.},
url = {http://dblp.uni-trier.de/db/conf/indin/indin2024.html#MostafizKLBJS24},
year = 2024
}
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