Which strategy automatically identifies and categorizes animals in photos?
An AI practitioner has a database of animal photos. The AI practitioner wants to automatically identify and categorize the animals in the photos without manual human effort. Which strategy meets these requirements?
Community Votes
100% of anonymous learners picked answer A. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
This question tests the ability to distinguish between computer vision tasks, specifically recognizing that object detection handles both identification and categorization of visual objects in images.
Object detection is the correct computer vision technique for automatically identifying, locating, and categorizing objects such as animals within images without manual effort. The community unanimously agrees that object detection perfectly matches the scenario of classifying animal photos.
Candidates unfamiliar with computer vision terminology might confuse object detection with anomaly detection, which is used to identify unusual patterns or outliers rather than classify known objects like animals.
Community Discussion (6 comments)
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Expert Analysis
Understanding the Scenario
The AI practitioner needs to automatically identify and categorize animals in a database of photos. This requires a computer vision technique that can: 1. Detect the presence of objects (animals) in images 2. Locate where those objects are within the image 3. Classify what type of animal each object represents
Why Object Detection is Correct
Object detection is a computer vision technique that combines image classification and localization. It identifies and draws bounding boxes around objects within an image while simultaneously assigning labels to those objects. In this scenario, object detection would:
- Scan each photo in the database
- Locate animal(s) within the images
- Categorize them (e.g., "dog," "cat," "bird," "elephant")
- Accomplish this entirely without manual human intervention
Why Other Options Are Incorrect
Anomaly detection (B) is designed to identify unusual patterns, outliers, or deviations from expected behavior. It would flag photos that don't match a "normal" pattern but wouldn't systematically categorize different animal types.
Named entity recognition (C) is a natural language processing (NLP) technique used to identify and classify named entities (people, organizations, locations) within text data—not images.
Inpainting (D) is an image editing technique used to reconstruct missing or damaged portions of an image. It has nothing to do with identifying or categorizing objects within images.
Community Consensus
The community voted 100% for option A, with multiple users confirming that object detection is the standard computer vision approach for identifying and categorizing visual content like animals in photographs.
Official Reference
Exam Strategy
When faced with computer vision questions, identify whether the task involves text (NLP), image modification (inpainting), outlier identification (anomaly detection), or object identification/categorization (object detection). The specific verbs in the question—'identify' and 'categorize'—directly point to object detection.
Related Analysis
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