A lightweight ultrasound welding surface defect detection network based robust feature downsampling

Key Points

• The method improves defect detection accuracy for ultrasound welding surfaces, showcasing enhanced sensitivity.
• Achieving up to 95% accuracy in detecting defects, this approach reduces false positives significantly.
• Utilizing a neural network with lightweight design and feature downsampling techniques for faster processing.
• The findings emphasize the potential of improved algorithms in industry applications for quality assurance.