Hybrid optoelectronic architecture with DMD optical convolution, compressed sensing, and CLIP alignment maintains defect detection accuracy while cutting data volume by 90% and computation by 60%.
Robust unsupervised anomaly detection for surface defects based on stacked broad learning system,
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An Integrated Hardware-Software Design for Low-Data Spatial Defect Detection in Robotic Visual Inspection with Hybrid Optoelectronic Neural Networks
Hybrid optoelectronic architecture with DMD optical convolution, compressed sensing, and CLIP alignment maintains defect detection accuracy while cutting data volume by 90% and computation by 60%.