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Showing 1 to 6 of 6 for “"Surface defect detection"”.

  1. Bridge Pier Surface Defect Detection Based on Improved YOLOV9

    This research introduces an innovative surface defect detection methodology specifically designed for bridge piers, which integrates state-of-the-art image enhancement algorithms with sophisticated target detection frameworks. This hybrid approach effectively addresses some of the inherent …

    uwtsd Repository record for Bridge Pier Surface Defect Detection Based on Improved YOLOV9 (opens in a new tab)

  2. Modelling visual search for surface defects

    … been done on developing algorithms for automated surface defect detection. However, comparisons between these models and human perception are rarely carried out. This thesis aims to investigate how well human observers can nd defects in textured surfaces, over a wide range of task di culties. …

    heriot-watt Repository record for Modelling visual search for surface defects (opens in a new tab)

  3. Robotic Inspection and Data Analytics to Localize and Visualize the Structural Defects of Civil Infrastructure

    … environments. In addition to GPR, visual-based surface defect detection plays a crucial role in assessing and maintaining civil infrastructure. To facilitate deployment on a robotic platform and enhance inspection capabilities, the integration of GPR and visual-based sensors, such as RGB-D …

    cuny Repository record for Robotic Inspection and Data Analytics to Localize and Visualize the Structural Defects of Civil Infrastructure (opens in a new tab)

  4. Leveraging Retrieval-Augmented Generation, Prompt Engineering, and Vision Language Models for Surface Defect Classification and Root Cause Analysis in Manufacturing

    … prompt-engineering strategies to enhance surface defect classification and Root Cause Analysis (RCA) in manufacturing. The research examines whether generative and multimodal Artificial Intelligence (AI) systems can deliver accurate, explainable, and cost efficient quality control for …

    stellenbosch Repository record for Leveraging Retrieval-Augmented Generation, Prompt Engineering, and Vision Language Models for Surface Defect Classification and Root Cause Analysis in Manufacturing (opens in a new tab)