What should you do?

Your company uses an Azure Cognitive Services solution to detect faces in uploaded images. The method to detect the faces uses the following code.

You discover that the solution frequently fails to detect faces in blurred images and in images that contain sideways faces.
You need to increase the likelihood that the solution can detect faces in blurred images and images that contain sideways faces.
What should you do?
A. Use a different version of the Face API.
B. Use the Computer Vision service instead of the Face service.
C. Use the Identify method instead of the Detect method.
D. Change the detection model.

Correct Answer: D
Explanation/Reference:
Explanation:
Evaluate different models.
The best way to compare the performances of the detection models is to use them on a sample dataset. We recommend calling the Face – Detect API on a variety of images, especially images of many faces or of faces that are difficult to see, using each detection model. Pay attention to the number of faces that each model returns.
The different face detection models are optimized for different tasks. See the following table for an overview of the differences.

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model