Research on the Application of Computer Vision in the Field of Intelligent Manufacturing
Authors: Zhang Wei, Li Na, Wang Fang, Chen Jing
With the rapid development of intelligent manufacturing, computer vision technology has become a key enabling technology for quality inspection, robot navigation, and process control. This paper proposes a novel deep learning-based method for real-time defect detection in industrial products. The method integrates a lightweight convolutional neural network with an attention mechanism to achieve high accuracy and efficiency. Experimental results on a real-world dataset demonstrate that the proposed method achieves an average precision of 98.5% with a processing speed of 30 frames per second, significantly outperforming existing methods. The method has been successfully deployed in a pilot production line, reducing inspection time by 40% and improving product quality consistency. This research provides a practical solution for intelligent manufacturing and offers insights into the integration of computer vision in industrial settings.
