AI-900 Question 18
Single answerA retail company wants to implement a solution where they can automatically detect when shelves in their stores are out of stock by analyzing camera feeds. Which computer vision workload is the most appropriate for this scenario?
- A
Optical Character Recognition (OCR)
- B
Object Detection
- C
Image Classification
- D
Semantic Segmentation
Show answer and explanation
Correct answer: B
Explanation
Object Detection is the most appropriate workload for this scenario because it can analyze video feeds from the store's cameras and identify specific objects (or the absence of objects) on the shelves, enabling the detection of out-of-stock situations in real-time.
- A. Incorrect.
Optical Character Recognition (OCR) is used to extract text from images or documents. While useful for reading product labels or receipts, it is not suitable for detecting objects like empty shelves.
- B. Correct.
Object Detection is the correct choice because it identifies specific objects within an image or video, such as detecting whether shelves are stocked or empty.
- C. Incorrect.
Image Classification assigns a single label to an entire image. It cannot locate or identify multiple objects within an image, such as detecting individual products on a shelf.
- D. Incorrect.
Semantic Segmentation provides pixel-level classification of an image, but it is often used for scenarios like autonomous driving or medical imaging, not for detecting stocked or empty shelves.