AI-102 Question 133
Single answerYou are tasked with developing a solution for a retail application that analyzes images of grocery shelves. The solution must identify and count each product type (e.g., soda cans, cereal boxes) on the shelf. Which type of model should you choose?
- A
Image classification
- B
Object detection
- C
Semantic segmentation
- D
Anomaly detection
Show answer and explanation
Correct answer: B
Explanation
Object detection is the most suitable model for this scenario because it can identify and localize individual items within an image, such as soda cans or cereal boxes, and count how many of each are present. Image classification is inadequate because it only assigns a single label to the entire image, and semantic segmentation would unnecessarily classify every pixel, which is not required for this task.
- A. Incorrect.
Image classification can only determine the overall category of an image (e.g., 'grocery shelf image with products') but cannot identify or count individual items within the image.
- B. Correct.
Object detection is the correct choice because it identifies and localizes individual objects (e.g., soda cans, cereal boxes) within an image, and can also provide a count of each object type.
- C. Incorrect.
Semantic segmentation is used for pixel-level classification of an image, which might be overkill for this scenario and doesn't focus on bounding boxes or counting objects.
- D. Incorrect.
Anomaly detection is used to identify unusual patterns or outliers in data, which is not relevant for identifying and counting products on a shelf.