Object Detection on Wafers is the application of object detection algorithms to locate and classify multiple defects or features in a single wafer image — predicting both the bounding box and class label for each defect, enabling rapid defect localization and categorization.

Key Object Detection Architectures

• YOLO (You Only Look Once): Single-pass detection for real-time performance.
• Faster R-CNN: Two-stage detector with region proposal + classification for higher accuracy.
• SSD (Single Shot Detector): Multi-scale feature map detection balancing speed and accuracy.
• Anchor-Free: FCOS, CenterNet — predict defect centers without predefined anchor boxes.

Why It Matters

• Multi-Defect: Detects and classifies all defects in one image simultaneously (unlike image classification which handles one per crop).
• Localization: Provides spatial coordinates for each defect — enables map generation.
• Production Speed: YOLO-based detectors achieve real-time performance for inline inspection.

Object Detection is find, locate, and classify in one step — applying modern detection architectures to simultaneously locate and categorize every defect in wafer images.