Abstract: Traditional crack detection methods often struggle with low efficiency and accuracy due to manual feature extraction and computational resource limitations. To overcome these challenges, we ...

Abstract: Object detection is a foundation process in computer vision having widespread applications in autonomous driving, medical diagnostics and security monitoring. Recent advancements and ...

Abstract: Detecting road cracks is crucial for ensuring road traffic safety and stability. However, currently existing detection methods do not usually pay close attention to the global, local and ...

Abstract: Road crack detection is crucial for infrastructure maintenance and traffic safety, yet existing methods struggle to balance detection accuracy and computational efficiency due to complex ...

Abstract: Pavement crack detection poses a formidable challenge due to the intricate texture structures of cracks and the complex environmental settings in which they are situated. In recent years, ...

I skipped adding the pad to the input image when resizing, which might affect the accuracy of the model if the input image has a different aspect ratio compared to the input size of the model. Always ...

When running ArUco marker detection (cv::aruco::ArucoDetector) in multithreaded contexts, memory usage increases significantly and is not released after threads complete. The leak does not occur in ...

download from this link the code: https://github.com/axolotl-git/CrackSearcher/archive/refs/heads/main.zip extract the zip somewhere on your computer Download python ...