A Study of Prompt Creation Method for Improving the Accuracy of Illegal dumping Image Classification by Large Vision Language Model

Abstract

In this study, we examined the effect of different prompts on detection accuracy with the aim of improving the accuracy of image classification using the Large Vision Language Model (LVLM) in the civil engineering and construction fields. The results suggest the effectiveness of using prompts that represent the objects to be detected by showing specific examples in the validation range. The results of this study suggest the effectiveness of using prompts that represent the objects to be detected by showing specific examples in the validation area.