과제정보
본 연구는 국토교통부/국토교통과학기술진흥원의 지원으로 수행되었음(과제번호200RPS-B158109-04).
The construction industry is increasingly adopting vision AI technologies to improve efficiency and safety management. However, the complex and dynamic nature of construction sites can pose challenges to the accuracy of vision AI models trained on datasets that do not consider the background. This study investigates the effect of background on object recognition for vision AI in construction sites by constructing a learning dataset and a test dataset with varying backgrounds. Frame scaffolding was chosen as the object of recognition due to its wide use, potential safety hazards, and difficulty in recognition. The experimental results showed that considering the background during model training significantly improved the accuracy of object recognition.
본 연구는 국토교통부/국토교통과학기술진흥원의 지원으로 수행되었음(과제번호200RPS-B158109-04).