Safety-Relevant AI-Based System Robustification with Neural Network Ensembles

被引：0

作者：

Aldoma, Adria ^{[1
,2
]}

Brando, Axel ^{[1
]}

Cazorla, Francisco J. ^{[1
]}

Abella, Jaume ^{[1
]}

机构：

[1] Barcelona Supercomp Ctr BSC, Barcelona, Spain

[2] Univ Politecn Catalunya UPC, Barcelona, Spain

来源：

2024 IEEE 30TH INTERNATIONAL SYMPOSIUM ON ON-LINE TESTING AND ROBUST SYSTEM DESIGN, IOLTS 2024 | 2024年

关键词：

D O I：

10.1109/IOLTS60994.2024.10616095

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Functional safety requirements of AI-based safety-critical applications challenge AI models, whose accuracy can be limited. In this paper, we show how using several cooperative deep learning (DL) models helps to raise global accuracy and reject making a prediction when confidence is below a pre-established threshold.

引用

页数：3

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