Detecting small targets and handling target occlusion and overlap are critical challenges in
weld defect detection. In this paper, we propose the S-YOLO model, a novel weld defect …

X-ray image plays an important role in manufacturing industry for quality assurance,
because it can reflect the internal condition of weld region. However, the shape and scale of …

Aiming at the problems of low target detection accuracy and high leakage rate of the current
traditional weld surface defect detection methods and existing detection models, an …

Welding defects can pose significant safety risks in the industrial production. Accurate
detection of these defects is crucial for ensuring the industrial production safety. Traditional …

Radiography testing for welding defect detection is an essential inspection procedure to
ensure welding quality. However, detecting these defects is a challenging task because they …

This work aims to improve the low accuracy caused by interference information during real-
time weld surface detection. First, a weld surface dataset with 7580 pictures containing eight …

Weld feature point detection is a key technology for welding trajectory planning and tracking.
Existing two-stage detection methods and conventional convolutional neural network (CNN) …

Pipeline is the main transportation. In order to ensure the safety of pipeline transportation,
the research on automatic recognition of defect features in X-ray film digital images has …

In this study, a deep convolutional neural network based on an improved You only look once
version 3 (YOLOv3) is proposed to improve the accuracy and real-time detection of small …

As industrial production becomes more modern and intelligent today, the inspection of
product quality of the workshop is becoming more and more accustomed to replacing the old …