CNN (Convolutional Neural Network)
Last updated 2026.02.13CNN합성곱신경망딥러닝컴퓨터비전불량검사품질관리영상인식deep learningcomputer visionquality inspection
Definition
CNN (Convolutional Neural Network) is a deep learning neural network that automatically learns data features through filter optimization. It specializes in recognizing patterns in various data types including images, video, and audio, and has become the de-facto standard in computer vision applications.
Manufacturing Applications
Automated Quality Inspection
- Visual inspection: Real-time detection of scratches, cracks, and contamination on product surfaces
- Weld quality inspection: Automatic identification of micro-defects such as porosity and cracks in welds
- Assembly verification: Visual validation of component position, orientation, and assembly status
Production Floor Monitoring
- Worker safety management: Detection of safety helmet/vest compliance and hazardous zone entry
- Inventory management: Automatic identification of material and finished goods types and quantities in warehouses
- Equipment anomaly detection: Early detection of equipment overheating, leakage through thermal imaging
Key Points
CNN replaces human visual inspection, enabling consistent quality standards 24/7. Particularly in high-precision industries such as semiconductors, displays, and automotive parts, it reduces inspection time by over 90% while improving defect detection rates. With transfer learning, models can be quickly built with minimal on-site data, making it highly effective for manufacturing environments.