diff --git a/Embedding.md b/Embedding.md
index d090ec9..4d95bd5 100644
--- a/Embedding.md
+++ b/Embedding.md
@@ -10,6 +10,8 @@ and calculate embedding vectors for both first and second image you want to comp
 To achieve quality results, it is also highly recommended to have `face.mesh` and `face.detection.rotation`  
 enabled as calculating feature vectors on non-quality inputs can lead to false results  
 
+Simmilarity match above 75% is considered good match while simmilarity match above 60% is considered best-guess  
+
 For example,
 
 ```js
@@ -92,7 +94,7 @@ To achieve optimal result, `Human` performs following operations on an image bef
 - Find precise face angle and again straighten face
 - Crop again with more narrow margins
 - Convert image to grayscale to avoid impact of different colorizations
-- Normalize brightness to common range for all images
+- Normalize brightness to full range for all images
 
 <br>
 
diff --git a/Outputs.md b/Outputs.md
index 6f08d04..9b829a8 100644
--- a/Outputs.md
+++ b/Outputs.md
@@ -33,8 +33,9 @@ result = {
           emotion,     // <string> 'angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'
         }
       ],
-      tensor:      // if config.face.detector.return is set to true, detector will
-                   // return a raw tensor containing cropped image of a face
+      tensor:      // if config.face.detector.return is set to true, detector will return
+                   // a raw tensor containing cropped image of a face
+                   // note that tensors must be explicitly disposed to free memory by calling tensor.dispose();
     }
   ],
   body:            // <array of detected objects>