Open-Set Recognition Model Based on Negative-Class Sample Feature Enhancement Learning Algorithm

Open-Set Recognition Model Based on Negative-Class Sample Feature Enhancement Learning Algorithm

In order to solve the problem that the F1-measure value and the AUROC value of some classical open-set classifier methods do not exceed 40% in high-openness scenarios, this paper proposes an algorithm combining negative-class feature enhancement learning and a Weibull distribution based on an extrem...

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Bibliographic Details
Main Authors: Guowei Yang, Shijie Zhou, Minghua Wan
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Mathematics
Subjects:
open-set recognition
enhancement learning
feature enhancement
extreme value distribution theory
Weibull distribution
Online Access:https://www.mdpi.com/2227-7390/10/24/4725

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