A case study of testing an image recognition application
Publication Date
1-1-2021
Document Type
Conference Proceeding
Publication Title
Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE
Volume
2021-July
DOI
10.18293/SEKE2021-194
First Page
560
Last Page
563
Abstract
High-quality Artificial intelligence (AI) software in different domains, like image recognition, has been widely emerged in our lives. They are built on machine learning models to implement intelligent features. However, the current research on image recognition software rarely discusses test questions, clear quality requirements, and verification methods. This paper presents a case study of a realistic image recognition application called Calorie Mama using manual and automation testing with a 3D decision table. The study results indicate the proposed method is feasible and effective in quality evaluation.
Funding Number
kfjj20201603
Funding Sponsor
Foundation of the Graduate Innovation Center, Nanjing University of Aeronautics and Astronautics
Keywords
AI software quality validation, Image recognition, Testing AI software
Department
Computer Engineering
Recommended Citation
Chuanqi Tao, Dongyu Cao, Hongjing Guo, and Jerry Gao. "A case study of testing an image recognition application" Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE (2021): 560-563. https://doi.org/10.18293/SEKE2021-194
