Jun 1, 2022 · This paper presents a generalized incremental 2DPCA algorithm and an online detection method for the recognition of weld surface defects.
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Jan 22, 2024 · An improved YOLOv7 pipeline weld surface defect detection model is proposed to improve detection results.
In this paper, we describe an automatic system to detect, recognise, and classify welding defects in radiographic images and evaluate the performance for ...
An in-situ weld surface defect recognition method is proposed in this paper based on an improved lightweight MobileNetV2 algorithm.
Missing: incremental | Show results with:incremental
In this paper, we describe an automatic detection system to recognise welding defects in radiographic images. In a first stage, image processing techniques, ...
To achieve this goal, an improved Yolo-graph convolution head (GCH) model is proposed based on the stable and fast Yolo-v5. The improvements primarily involve ...
In this paper, an online surface defects detection method based on YOLOV3 is proposed. Firstly, using lightweight network MobileNetV2 to replace the original ...
Missing: weld | Show results with:weld
Jul 14, 2023 · This study proposes an automated approach to identify multi-class welding defects by processing the X-ray images.
Nov 9, 2022 · This paper proposes to combine deformable network, FPN network and ResNet50 to improve the detection performance of the algorithm for multi-scale targets, ...
In this paper, the state-of-the-art single-stage object detection algorithm YOLOv5 is proposed to be applied to the field of steel pipe weld defect detection.