Explanation:
The correct mappings are based on the Microsoft Azure AI Fundamentals (AI-900) curriculum topic:
"Describe features of computer vision workloads." Microsoft divides computer vision tasks into key workload types - image classification, object detection, facial recognition, and optical character recognition (OCR) - each designed for specific visual analysis objectives.
* Identify celebrities in images # Facial recognitionFacial recognition goes beyond simple face detection; it can identify or verify specific individuals by comparing facial features with known profiles.
According to Microsoft Learn, the Face service in Azure Cognitive Services can detect, recognize, and identify people in photos or videos. Recognizing celebrities or known individuals is a prime example of facial recognition.
* Extract movie title names from movie poster images # Optical Character Recognition (OCR)OCR is used to detect and extract text content from images, such as printed or handwritten words. Azure's Computer Vision API uses OCR technology to read text in various languages from photos, scanned documents, or posters. Therefore, extracting movie titles or actor names from a poster image is a perfect use case for OCR.
* Locate vehicles in images # Object detectionObject detection identifies and locates specific objects within an image, returning bounding boxes that indicate their positions. In Azure, the Custom Vision service or Computer Vision object detection models are used to detect multiple objects like vehicles, pedestrians, or animals in a single image.
Summary:
* Facial recognition # Identifies specific people (celebrities)
* OCR # Extracts text (movie titles)
* Object detection # Finds and locates physical items (vehicles)
Thus, the verified and official answer is: