The correct answers are B. assigning the color pixels in an image to object names and C. describing the contents of an image.
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Describe features of computer vision workloads on Azure," computer vision is a branch of AI that enables systems to analyze, interpret, and understand visual data from images and videos. It allows machines to identify objects, people, text, and even describe scenes automatically.
* Option B: Assigning color pixels in an image to object names represents image classification or object detection, which are key computer vision workloads. In these tasks, AI analyzes pixel patterns to determine which pixels correspond to specific objects (for example, classifying pixels as "car," "tree," or "road").
* Option C: Describing the contents of an image corresponds to image captioning, another computer vision workload. It involves using AI models trained to generate natural language descriptions of what is visible in an image, such as "A group of people sitting at a dining table." Azure's Computer Vision service provides this functionality through its "Describe Image" API.
Incorrect options:
* A. Creating photorealistic images involves generative AI and 3D modeling, not traditional computer vision.
* D. Detecting inconsistencies and anomalies in a data stream relates to anomaly detection, not computer vision.
* E. Creating visual representations of numerical data involves data visualization, not AI-driven image analysis.