Exam AI-900 topic 1 question 192 discussion

Analysis

Analysys

Analysis should be the correct answer.

Análisis -> https://learn.microsoft.com/es-es/training/modules/detect-analyze-faces/3-face-analysis-azure

Copilot: It sounds like you’re describing an AI solution that leverages facial recognition technology. This type of AI can analyze portrait photographs to provide feedback on various aspects such as exposure, noise, and occlusion, helping photographers enhance the quality of their images.

as per copilot, it is detection

Detection https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/concept-face-detection#attributes

I think analysis is the most accurate, but who knows.. i have an exam tomorrow and i still don't know whether analysis or detection is the most correct one.

Answer : Analysis An AI solution that helps photographers to take better pictures by providing feedback on exposure, noise, and occlusion is an example of facial "analysis" or "photo analysis." In this context, the AI system is analyzing the photo quality and characteristics, such as exposure (brightness and contrast), noise (graininess or pixel-level disturbances), and occlusion (obstructions or unwanted objects). The AI's analysis can then provide feedback to the photographer to improve the composition and settings, resulting in better photographs. While this specific example focuses on photo quality aspects, facial analysis may also involve analyzing and detecting faces within images, recognizing facial expressions, emotions, or attributes, but that doesn't seem to be the focus in this particular case.

It doesnt really matter which it is as Microsoft discontinues these parts of concept face detection. Question therefore outdated. "Microsoft will be retiring facial recognition capabilities that can be used to try to infer emotional states and identity attributes which, if misused, can subject people to stereotyping, discrimination or unfair denial of services. These include capabilities that predict emotion, gender, age, smile, facial hair, hair and makeup. Existing customers have until June 30, 2023 to discontinue use of these capabilities before they are retired. " https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-face-detection

Same as Question 186. https://www.examtopics.com/discussions/microsoft/view/100263-exam-ai-900-topic-1-question-186-discussion

1. detection https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview-identity#face-detection-and-analysis Face detection is required as a first step in all the other scenarios. The Detect API detects human faces in an image and returns the rectangle coordinates of their locations. It also returns a unique ID that represents the stored face data. This is used in later operations to identify or verify faces. Optionally, face detection can extract a set of face-related attributes, such as head pose, age, emotion, facial hair, and glasses. These attributes are general predictions, not actual classifications. Some attributes are useful to ensure that your application is getting high-quality face data when users add themselves to a Face service. For example, your application could advise users to take off their sunglasses if they're wearing sunglasses.

I think facial analysis is correct in this question because the Face service, although it has now evolved and includes it in Detection, used to have a specific facial analysis service as part of the Face API. And I don't think this question is that up-to-date, otherwise it wouldn't even be there among the Facial Analysis answers.

Looks like face detection: https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-face-detection

Looking at the Detect API, it responds with exposure and occlusion, so I think facial detection is correct. https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236

Analysis

Analysis