AI-900 Question 148
Select 2A retail company wants to implement a computer vision solution to automatically monitor their stores for detecting when shelves are empty and need restocking. Which type(s) of computer vision solutions would be most appropriate for this scenario?
- A
Object detection
- B
Image classification
- C
Optical character recognition (OCR)
- D
Semantic segmentation
- E
Facial recognition
Show answer and explanation
Correct answers: A, D
Explanation
To monitor shelves for restocking, the solution needs to identify specific objects (e.g., empty or stocked shelves) and potentially classify regions of an image. Object detection can locate and identify these objects, while semantic segmentation can categorize areas within an image, making both solutions suitable for this scenario.
- A. Correct.
Object detection is the correct choice as it identifies and locates specific objects (e.g., products or empty shelves) in an image or video, which is necessary for detecting empty shelves.
- B. Incorrect.
Image classification is not sufficient on its own for this task. It assigns a single label to an entire image but cannot locate or monitor specific objects like empty shelves in a store.
- C. Incorrect.
Optical character recognition (OCR) is used to extract text from images and is unrelated to detecting objects or empty shelves in a retail store.
- D. Correct.
Semantic segmentation is also correct because it can classify each pixel in an image into categories, which could help identify regions of empty shelves versus stocked shelves.
- E. Incorrect.
Facial recognition is irrelevant in this context as it is used for identifying or verifying individuals by their facial features, not for detecting objects or empty shelves.