Oct 13, 2023 · In this study, the Swin_YOLOv5 model performed the best with an F1 score of 98.5%, a recall rate of 98.4%, and a precision of 98.7%, and ...
Oct 13, 2023 · In this study, the Swin_YOLOv5 model performed the best with an F1 score of 98.5%, a recall rate of 98.4%, and a precision ...
Apr 19, 2024 · This study aimed to address the problems of low detection accuracy and inaccurate positioning of small-object detection in remote sensing images ...
This research group used a combination of Multiple Screen Shots and Swin_YOLOv5_to recognise asphalt pavement voids in real time and achieved an accuracy ...
Apr 18, 2024 · Abstract—Detecting buried objects using ground-penetrating radar (GPR) profiles typically requires manual interaction and considerable time.
May 6, 2024 · Shengjie Xu: Real-Time Detection of Voids in Asphalt Pavement Based on Swin-Transformer-Improved YOLOv5. IEEE Trans. Intell. Transp. Syst ...
Abstract. Accurate pavement surface crack detection is crucial for analyzing pavement survey data and the development of maintenance strategies.
Sep 21, 2023 · This paper presents an improved deep neural network model based on YOLOv5 for real-time road pavement damage detection in photographic representations of ...
Missing: Voids | Show results with:Voids
To address crack diversity, Wang et al. [15] proposed a detector combining YOLOv5 with a Vision Transformer (ViT) to calculate attention weights for ...
Missing: Swin- | Show results with:Swin-
Apr 19, 2024 · The approach uses Swin Transformer as a feature extraction network and utilizes the YOLOX object detection algorithm as a road underground ...