A case study of testing an image recognition application
Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE
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.
Foundation of the Graduate Innovation Center, Nanjing University of Aeronautics and Astronautics
AI software quality validation, Image recognition, Testing AI software
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