Identification of out-of-distribution cases of CNN using class-based surprise adequacy

Marhaba, Mira; Merlo, Ettore; Khomh, Foutse; Antoniol, Giuliano; Marhaba, Mira; Merlo, Ettore; Khomh, Foutse; Antoniol, Giuliano

Identification of out-of-distribution cases of CNN using class-based surprise adequacy

Mira Marhaba, Ettore Merlo , Foutse Khomh , Giuliano Antoniol

Paper (2022)

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Department:

Department of Chemical Engineering
Department of Computer Engineering and Software Engineering

ISBN:

9781450392754

PolyPublie URL:

https://publications.polymtl.ca/51463/

Conference Title:

IEEE/ACM 1st International Conference on AI Engineering - Software Engineering for AI (CAIN 2022)

Conference Location:

Pittsburgh, PA, USA

Conference Date(s):

2022-05-16 - 2022-05-17

Publisher:

IEEE

DOI:

10.1145/3522664.3528617

Official URL:

https://doi.org/10.1145/3522664.3528617

OAI:

oai:publications.polymtl.ca:51463

ORCID

Date Deposited:

18 Apr 2023 14:59

Last Modified:

14 Oct 2026 14:08

Cite in APA 7:

Marhaba, M., Merlo, E., Khomh, F., & Antoniol, G. (2022, May). Identification of out-of-distribution cases of CNN using class-based surprise adequacy [Paper]. IEEE/ACM 1st International Conference on AI Engineering - Software Engineering for AI (CAIN 2022), Pittsburgh, PA, USA. https://doi.org/10.1145/3522664.3528617

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