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Libra-cam: An activation-based attribution based on the linear approximation of deep neural nets and threshold calibration
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Lee, Sangkyun | - |
| dc.date.accessioned | 2022-11-13T12:41:01Z | - |
| dc.date.available | 2022-11-13T12:41:01Z | - |
| dc.date.created | 2022-11-12 | - |
| dc.date.issued | 2022-07-26 | - |
| dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/145296 | - |
| dc.publisher | International Joint Conferences on Artificial Intelligence Organization | - |
| dc.title | Libra-cam: An activation-based attribution based on the linear approximation of deep neural nets and threshold calibration | - |
| dc.title.alternative | Libra-cam: An activation-based attribution based on the linear approximation of deep neural nets and threshold calibration | - |
| dc.type | Conference | - |
| dc.contributor.affiliatedAuthor | Lee, Sangkyun | - |
| dc.identifier.bibliographicCitation | International Joint Conference on Artificial Intelligence (IJCAI), pp.3185 - 3191 | - |
| dc.relation.isPartOf | International Joint Conference on Artificial Intelligence (IJCAI) | - |
| dc.relation.isPartOf | Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence | - |
| dc.citation.title | International Joint Conference on Artificial Intelligence (IJCAI) | - |
| dc.citation.startPage | 3185 | - |
| dc.citation.endPage | 3191 | - |
| dc.citation.conferencePlace | AU | - |
| dc.citation.conferencePlace | Vienna | - |
| dc.citation.conferenceDate | 2022-07-23 | - |
| dc.type.rims | CONF | - |
| dc.description.journalClass | 1 | - |
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