深度迁移学习下的船舶焊接表面缺陷智能检测系统

为提升船舶焊接表面缺陷检测的智能化水平、更好地适应智能制造需求，设计船舶焊接表面缺陷智能检测系统。通过采集船舶焊接表面图像，对图像进行预处理，结合深度迁移学习方法，根据缺陷特征对船舶焊接表面缺陷进行分析，建立检测模型，对图像进行缺陷目标检测，从而得到一种船舶焊接表面缺陷智能检测的高效手段，为船舶制造智能化水平和先进性的提升提供驱动力。

Intelligent Detection System of Ship Welding Surface Defect Under Deep Transfer Learning

In order to improve the intelligentization level of ship welding surface defect detection and better meet the intelligent manufacturing needs, the intelligent detection system of ship welding surface defect is designed. Through gathering the ship welding surface images and preprocessing the images, combined with the deep transfer learning method, the ship welding surface defect is analyzed according to the defect characteristics, and the detection model is established to conduct the defect target detection for the images, so as to get an efficient means of intelligent detection of ship welding surface defect, which provides driving force for the improvement of shipbuilding intelligentization level and advanced nature.