Learn how to select Azure AI models for tasks like identifying sports equipment, counting items, and recognizing high-value products. Essential knowledge for acing the AI-102 exam and building smarter AI solutions.
Table of Contents
Question
Xerigon Corporation is developing an AI-powered application to assist in warehouse management of used sports equipment. The application needs to process images of boxes of equipment that are received at the warehouse.
Task 1: Identify whether a box contains equipment for baseball, football, hockey, or some other sport or a combination of different sports.
Task 2: Detect and count the items in the box.
Task 3: Identify equipment that has a high resale value so that this equipment can be refurbished first.
Which Azure AI model type should you choose for each task?
Drag the model to the appropriate task.
Custom Model type:
- Object detection
- Image classification
- Product recognition
Answer
Task 1: Image classification
Task 2: Object detection
Task 3: Product recognition
Explanation
Image classification models are designed to analyze the overall content of an image and classify it into categories, such as specific types of sports equipment. This approach is efficient for making binary or categorical decisions based on the content of the entire image.
Object detection models are designed to identify and locate multiple objects within a single image, providing bounding boxes around each detected item. This model can count the number of objects in a box.
Product recognition models are similar to the object detection model but can be used to recognize brand names and product labels. You can use predictions for product recognition to specify location and class labels.
Microsoft Azure AI Engineer Associate AI-102 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Engineer Associate AI-102 exam and earn Microsoft Azure AI Engineer Associate AI-102 certification.