early iterations since the model might produce a huge number of false alarms
while the detector is still bad.  Processing all these detections can cause it
to run slowly until the model is good enough to avoid really excessive amounts
of false alarms.  This change puts more of a limit on the number of false
alarms processed during those early iterations and avoids the slowdown.