diff --git a/dlib/dnn/loss.h b/dlib/dnn/loss.h
index 95177705b..6f62c6701 100644
--- a/dlib/dnn/loss.h
+++ b/dlib/dnn/loss.h
@@ -725,6 +725,7 @@ namespace dlib
             DLIB_CASSERT(input_tensor.num_samples() == output_tensor.num_samples());
             DLIB_CASSERT(output_tensor.k() == (long)options.detector_windows.size());
 
+            double det_thresh_speed_adjust = 0;
 
 
             // we will scale the loss so that it doesn't get really huge
@@ -741,9 +742,17 @@ namespace dlib
             std::vector<intermediate_detection> dets;
             for (long i = 0; i < output_tensor.num_samples(); ++i)
             {
-                tensor_to_dets(input_tensor, output_tensor, i, dets, -options.loss_per_false_alarm, sub);
+                tensor_to_dets(input_tensor, output_tensor, i, dets, -options.loss_per_false_alarm + det_thresh_speed_adjust, sub);
 
                 const unsigned long max_num_dets = 50 + truth->size()*5;
+                // Prevent calls to tensor_to_dets() from running for a really long time
+                // due to the production of an obscene number of detections.
+                const unsigned long max_num_initial_dets = max_num_dets*100;
+                if (dets.size() >= max_num_initial_dets)
+                {
+                    det_thresh_speed_adjust = std::max(det_thresh_speed_adjust,dets[max_num_initial_dets].detection_confidence + options.loss_per_false_alarm);
+                }
+
 
                 // The loss will measure the number of incorrect detections.  A detection is
                 // incorrect if it doesn't hit a truth rectangle or if it is a duplicate detection