AI-900 Question 149
Select 2A retail company wants to implement a solution to automatically monitor store shelves, detect low-stock items, and identify misplaced products in real-time. Which types of computer vision solutions would be most suitable for this scenario?
- A
Image classification
- B
Object detection
- C
Semantic segmentation
- D
Optical character recognition (OCR)
- E
Facial recognition
Show answer and explanation
Correct answers: B, C
Explanation
For this scenario, object detection is ideal for identifying and locating items on shelves, while semantic segmentation provides detailed information about the layout and placement of items. These two types of computer vision solutions are well-suited for solving problems related to inventory monitoring and shelf organization.
- A. Incorrect.
Image classification assigns a single label to an entire image but does not provide detailed information about the location of objects or specific segmentation. This would not be sufficient for monitoring shelf stock or detecting misplaced items.
- B. Correct.
Object detection identifies and localizes multiple objects in an image, making it suitable for detecting low-stock items and misplaced products on shelves.
- C. Correct.
Semantic segmentation classifies each pixel of an image into a category, which can help identify the exact layout of items on a shelf and detect misplaced products.
- D. Incorrect.
Optical character recognition (OCR) is used for extracting text from images but is not directly relevant for detecting low-stock or misplaced items.
- E. Incorrect.
Facial recognition is used for identifying or verifying people based on facial features, which is not applicable to the given scenario.