Publication:
Noise tolerant ternary weight deep neural networks for analog in-memory inference
| cris.virtual.department | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| cris.virtual.department | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| cris.virtual.department | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| cris.virtual.department | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| cris.virtual.department | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| cris.virtual.department | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| cris.virtual.department | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| cris.virtual.department | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| cris.virtual.orcid | 0000-0001-6567-2746 | |
| cris.virtual.orcid | 0000-0002-0742-9366 | |
| cris.virtual.orcid | 0000-0002-6792-7965 | |
| cris.virtual.orcid | 0000-0002-9876-3684 | |
| cris.virtual.orcid | 0000-0003-3825-5554 | |
| cris.virtual.orcid | 0000-0002-3861-0168 | |
| cris.virtual.orcid | 0000-0002-1592-755X | |
| cris.virtual.orcid | #PLACEHOLDER_PARENT_METADATA_VALUE# | |
| cris.virtualsource.department | 15ed05fe-d942-45fb-b815-bd96cf6bf1c6 | |
| cris.virtualsource.department | dd58335d-8a2a-4401-8914-5de314f80d91 | |
| cris.virtualsource.department | 7386c741-e8e9-427f-bca4-f091a80818f8 | |
| cris.virtualsource.department | c15adfc8-dbff-4360-af46-216cba7ed85c | |
| cris.virtualsource.department | cd229996-283c-420d-b3a4-343d55a60b34 | |
| cris.virtualsource.department | b1e77fca-3064-486a-843f-8df6743d3ff2 | |
| cris.virtualsource.department | 15e57581-19c6-4927-9cf5-286e171d9d9e | |
| cris.virtualsource.department | 10bf1a8b-0b83-4356-9bc9-0f8493cfc107 | |
| cris.virtualsource.orcid | 15ed05fe-d942-45fb-b815-bd96cf6bf1c6 | |
| cris.virtualsource.orcid | dd58335d-8a2a-4401-8914-5de314f80d91 | |
| cris.virtualsource.orcid | 7386c741-e8e9-427f-bca4-f091a80818f8 | |
| cris.virtualsource.orcid | c15adfc8-dbff-4360-af46-216cba7ed85c | |
| cris.virtualsource.orcid | cd229996-283c-420d-b3a4-343d55a60b34 | |
| cris.virtualsource.orcid | b1e77fca-3064-486a-843f-8df6743d3ff2 | |
| cris.virtualsource.orcid | 15e57581-19c6-4927-9cf5-286e171d9d9e | |
| cris.virtualsource.orcid | 10bf1a8b-0b83-4356-9bc9-0f8493cfc107 | |
| dc.contributor.author | Doevenspeck, Jonas | |
| dc.contributor.author | Vrancx, Peter | |
| dc.contributor.author | Laubeuf, Nathan | |
| dc.contributor.author | Mallik, Arindam | |
| dc.contributor.author | Debacker, Peter | |
| dc.contributor.author | Verkest, Diederik | |
| dc.contributor.author | Lauwereins, Rudy | |
| dc.contributor.author | Dehaene, Wim | |
| dc.contributor.imecauthor | Doevenspeck, Jonas | |
| dc.contributor.imecauthor | Vrancx, Peter | |
| dc.contributor.imecauthor | Laubeuf, Nathan | |
| dc.contributor.imecauthor | Mallik, Arindam | |
| dc.contributor.imecauthor | Debacker, Peter | |
| dc.contributor.imecauthor | Verkest, Diederik | |
| dc.contributor.imecauthor | Lauwereins, Rudy | |
| dc.contributor.imecauthor | Dehaene, Wim | |
| dc.contributor.orcidimec | Vrancx, Peter::0000-0002-9876-3684 | |
| dc.contributor.orcidimec | Debacker, Peter::0000-0003-3825-5554 | |
| dc.contributor.orcidimec | Laubeuf, Nathan::0000-0002-1592-755X | |
| dc.contributor.orcidimec | Mallik, Arindam::0000-0002-0742-9366 | |
| dc.contributor.orcidimec | Verkest, Diederik::0000-0001-6567-2746 | |
| dc.contributor.orcidimec | Lauwereins, Rudy::0000-0002-3861-0168 | |
| dc.date.accessioned | 2023-08-10T08:21:27Z | |
| dc.date.available | 2023-06-20T10:36:27Z | |
| dc.date.available | 2023-08-10T08:21:27Z | |
| dc.date.issued | 2021 | |
| dc.identifier.doi | 10.1109/IJCNN52387.2021.9533684 | |
| dc.identifier.eisbn | 978-0-7381-3366-9 | |
| dc.identifier.issn | 2161-4393 | |
| dc.identifier.uri | https://imec-publications.be/handle/20.500.12860/41948 | |
| dc.publisher | IEEE | |
| dc.source.conference | International Joint Conference on Neural Networks (IJCNN) | |
| dc.source.conferencedate | JUL 18-22, 2021 | |
| dc.source.conferencelocation | Shenzhen | |
| dc.source.journal | na | |
| dc.source.numberofpages | 8 | |
| dc.title | Noise tolerant ternary weight deep neural networks for analog in-memory inference | |
| dc.type | Proceedings paper | |
| dspace.entity.type | Publication | |
| Files | ||
| Publication available in collections: |