Image Augmentation as Test Generation for Deep Learning-Based Image Retrieval Systems
The findings provide practical guidelines for selecting augmentation techniques that maximize test diversity while preserving realistic image characteristics, thereby enabling the construction of comprehensive and effective test suites for image retrieval systems while reducing the cost of manual data labeling through...