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3129-2023 - IEEE Standard for Robustness Testing and Evaluation of Artificial Intelligence (AI)-based Image Recognition Service | IEEE Standard | IEEE Xplore

3129-2023 - IEEE Standard for Robustness Testing and Evaluation of Artificial Intelligence (AI)-based Image Recognition Service

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Abstract:

Test specifications with a set of indicators for common corruption and adversarial attacks, which can be used to evaluate the robustness of artificial intelligence-based ...Show More
Scope:This standard provides test specifications with a set of indicators for interference and adversarial attacks that can be used to evaluate the robustness of artificial int...Show More
Purpose:The purpose of this standard is to guide individuals and organizations who provide, develop, or use AI-based image recognition services in testing and evaluating these se...Show More

Abstract:

Test specifications with a set of indicators for common corruption and adversarial attacks, which can be used to evaluate the robustness of artificial intelligence-based image recognition services are provided in this standard. Robustness attack threats and establishes an assessment framework to evaluate the robustness of artificial intelligence-based image recognition service under various settings are also specified in this standard.
Scope:
This standard provides test specifications with a set of indicators for interference and adversarial attacks that can be used to evaluate the robustness of artificial intelligence (AI)-based image recognition services. This standard specifies robustness requirements and establishes an assessment framework to evaluate the robustness of AI-based image recognition services under various settings.
Purpose:
The purpose of this standard is to guide individuals and organizations who provide, develop, or use AI-based image recognition services in testing and evaluating these services and in improving the robustness of these services. It is also applicable to guide third-party evaluation laboratories to test and evaluate the robustness of the service by applying standards-based testing to score individual algorithmic implementations.
Date of Publication: 02 June 2023
Electronic ISBN:978-1-5044-9752-7
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=10141537

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