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What is IJPRT about?

This research paper evaluates digital image processing (DIP) and deep learning (DL) techniques for assessing pavement macrotexture and estimating air voids. It finds that the Edge Density Method offers the highest predictive accuracy among traditional DIP methods, while DL methods significantly outperform in air void estimation. The study presents a novel framework that combines these techniques to enhance real-time pavement analysis accuracy and scalability.

Author

MypatiVamsi

Language

EN