Confidence Estimation via Auxiliary Models
Reliably quantifying the confidence of deep neural classifiers is a challenging yet fundamental requirement for deploying such models in safety-critical applications. In this paper, we introduce a novel target criterion for model confidence, namely the true class probability (TCP). We show that TCP...
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Détails bibliographiques
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 44(2022), 10 vom: 04. Okt., Seite 6043-6055
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| Auteur principal: |
Corbiere, Charles
(Auteur) |
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| Autres auteurs: |
Thome, Nicolas,
Saporta, Antoine,
Vu, Tuan-Hung,
Cord, Matthieu,
Perez, Patrick |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2022
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
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| Sujets: | Journal Article |
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