AI Defect Detection (CNN)
Deep-learning detection of scratches, dents and stains on random surfaces where traditional methods fall short — with a 98% success rate.
Derin ÖğrenmeCNNAnomali Tespiti%98 Başarı
AI where geometry ends
When surfaces vary randomly — castings, leather, textiles, painted sheet — rule-based systems struggle to isolate scratches, dents, tears or oil stains. A deep-learning model trained on sample defect images catches what the human eye catches, far faster than human speed.
%98Defect-detection success rate
CNNConvolutional neural network architecture
ONNXIndustry-standard model runtime
GPUReal-time inference
Trained on your own data
The system is trained with good/defective samples collected from your line; anomaly-based approaches need only images of good parts. The model is retrained as production evolves, forming a living quality wall. Contact us for a demo.
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