To fine-tune the detection tool, do as follows:

1. Select a recognition algorithm (1):
   
   ALG1 is faster but less accurate while
   ALG2 is more accurate but relatively slower.
2. Set up false mask detections filtering:
   1. To apply filters, set Yes for the False mask detections filtering parameter (2).
   2. Set the minimal percentage of probability which makes the additional algorithm identify a track as a masked face in the Minimum filtering threshold for face mask detection field (7).   If the algorithm takes a decision that the track relates to a masked face with a probability value lower than the specified threshold, the track will be ignored. Set the value by trial-and-error, values over 30 are recommended.
3. Set the minimum threshold value for mask detection (3). Set a value by trial-and-error, values over 70 are recommended.
4. Set the minimum quality of a facial image for recognition with a mask (4, see Configuring masks detection). Set the value by trial-and-error, values over 30 are recommended.
5. Set the minimum quality of a facial image for recognition without a mask (5). Set the value by trial-and-error, values over 50 are recommended.
6. If you need to filter out false positives, set the minimum percentage of probability which makes the algorithm identify a track as a human face in the Minimum filtering threshold field (6, see Configure Facial Recognition). If the algorithm takes a decision that the track relates to a face with a probability value lower than the specified threshold, the track will be ignored. Set the value by trial-and-error, values over 50 are recommended.
7. Click the Apply button.