diff --git a/dlib/simd/simd8f.h b/dlib/simd/simd8f.h
index adbc28d0e..628ba74ee 100644
--- a/dlib/simd/simd8f.h
+++ b/dlib/simd/simd8f.h
@@ -125,8 +125,8 @@ namespace dlib
                 return _high[idx-4];
         }
 
-        inline simd4f low() const { return _low; }
-        inline simd4f high() const { return _high; }
+        inline const simd4f& low() const { return _low; }
+        inline const simd4f& high() const { return _high; }
 
     private:
         simd4f _low, _high;
@@ -141,8 +141,8 @@ namespace dlib
         inline simd8f_bool(const simd4f_bool& low_, const simd4f_bool& high_): _low(low_),_high(high_){}
 
 
-        inline simd4f_bool low() const { return _low; }
-        inline simd4f_bool high() const { return _high; }
+        inline const simd4f_bool& low() const { return _low; }
+        inline const simd4f_bool& high() const { return _high; }
     private:
         simd4f_bool _low,_high;
     };
diff --git a/dlib/simd/simd8i.h b/dlib/simd/simd8i.h
index 8fefa2644..18c06ec7e 100644
--- a/dlib/simd/simd8i.h
+++ b/dlib/simd/simd8i.h
@@ -91,8 +91,8 @@ namespace dlib
                 return _high[idx-4];
         }
 
-        inline simd4i low() const { return _low; }
-        inline simd4i high() const { return _high; }
+        inline const simd4i& low() const { return _low; }
+        inline const simd4i& high() const { return _high; }
 
     private:
         simd4i _low, _high;
diff --git a/examples/dnn_mmod_train_find_cars_ex.cpp b/examples/dnn_mmod_train_find_cars_ex.cpp
index 16419477a..b97e25a85 100644
--- a/examples/dnn_mmod_train_find_cars_ex.cpp
+++ b/examples/dnn_mmod_train_find_cars_ex.cpp
@@ -124,7 +124,7 @@ int main(int argc, char** argv) try
     // 
     // To explain this non-max suppression idea further it's important to understand how
     // the detector works.  Essentially, sliding window detectors scan all image locations
-    // and ask "is there a care here?".  If there really is a car in a specific location in
+    // and ask "is there a car here?".  If there really is a car in a specific location in
     // an image then usually many slightly different sliding window locations will produce
     // high detection scores, indicating that there is a car at those locations.  If we
     // just stopped there then each car would produce multiple detections.  But that isn't