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Biometric Systems/notes/2. Performance indexes.md

@@ -63,7 +63,7 @@ each point is paired with the most convenient one. It's not necessarily that poi
 
 ##### Comparing the results of submitting a template to a Deep Learning model
 - if using deep learning we should use the architecture to extract the embeddings (for both gallery and probe templates): we can delete the classification layer in order to get the embeddings that the architecture would use for the final classification.
-- mbeddings can be compard as they were vectors of hand-crafted features.
+- embeddings can be compard as they were vectors of hand-crafted features.
 
 ### Possible errors: verification
 - Genuine Match (GM, GA): the claimed identity is true and subject is accepted
@@ -103,9 +103,9 @@ What if ERR in two systems is the same, but the curves are different?
 We can use ROC curve or DET curve.
 For ROC, we can compute the area below the curve and use it as a metric, the higher the better.
 
-#### Possible errors: identificaiton - open set
+#### Possible errors: identification - open set
 In an open set identification task, the system determines if the individual's biometric signature matches a signature of someone in the gallery.
-The individual **does not make** and identity claim.
+The individual **does not make** an identity claim.
 - More possible error situations, depending on the matcher and on the threshold
 - A problem may occur if the system returns more possible candidates below the threshold. Who is the right one?
 > [!PDF|yellow] [[LEZIONE2_Indici_di_prestazione.pdf#page=27&selection=0,8,9,8&color=yellow|LEZIONE2_Indici_di_prestazione, p.27]]