d1) Neural Networks (Cont.5)
4. Select up to 250 of these subimages at random, apply the preprocessing steps and add them into the training set as negative examples. Go to step 2.
Stage 2. False detection elimination.
2.1. Merging overlapping detections:
- Count the number of detections within a specified neighborhood.
- A threshold determine if a location represents a face.