Ghouthi Boukli Hacene, François Leduc-Primeau
, Amal Ben Soussia, Vincent Gripon and François Gagnon
Paper (2019)
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| Department: | Department of Electrical Engineering |
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| Research Center: | GR2M - Microelectronics and Microsystems Research Group |
| PolyPublie URL: | https://publications.polymtl.ca/43651/ |
| Conference Title: | IEEE International Symposium on Circuits and Systems (ISCAS 2019) |
| Conference Location: | Sapporo, Japan |
| Conference Date(s): | 2019-05-26 - 2019-05-29 |
| Publisher: | IEEE |
| DOI: | 10.1109/iscas.2019.8702382 |
| Official URL: | https://doi.org/10.1109/iscas.2019.8702382 |
| Date Deposited: | 18 Apr 2023 15:02 |
| Last Modified: | 25 Sep 2024 16:30 |
| Cite in APA 7: | Hacene, G. B., Leduc-Primeau, F., Soussia, A. B., Gripon, V., & Gagnon, F. (2019, May). Training modern deep neural networks for memory-fault robustness [Paper]. IEEE International Symposium on Circuits and Systems (ISCAS 2019), Sapporo, Japan (5 pages). https://doi.org/10.1109/iscas.2019.8702382 |
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