Abstract: Accurately identifying sealed cracks on asphalt pavement surfaces is of significant importance to pavement management. This paper proposes an efficient semantic segmentation model called Parallel-TDNet for pixel-level ...

Abstract: This paper introduces DLANet, an algorithm for semantic segmentation designed to enhance the pixel-level detection of sealing cracks. DLANet extends the DeepLabV3+ encoder-decoder architecture by integrating four different ...

Abstract: Precise crack identification on intricate asphalt pavements poses a significant challenge for intelligent pavement distress detection. This paper proposes the CellNet, a deep learning model designed to offer an effective ...

Abstract: Accurate recognition and location of pavement manholes are of great significance for pavement maintenance. This paper proposes an improved You only look once X (YOLOX) for automated detection of manholes on asphalt pavements. ...