Free AWS AIF-C01 Certified AI Practitioner Actual Exam Questions - Question 2 Discussion
identify and categorize the animals in the photos without manual human effort.
Which strategy meets these requirements?
A. Object detection is the best fit since it not only identifies animals but also categorizes them automatically without human input. The other choices don’t really match: anomaly detection looks for weird or rare items, named entity recognition works with text, and inpainting is about filling image gaps. Even if the question doesn’t mention needing exact locations, object detection still covers recognizing and labeling animals directly in images, which meets the requirement better than anything else here.
Not B, since anomaly detection is about spotting outliers, not sorting animals into categories. Object detection (A) fits best because it can find and label each animal automatically.
Actually, I’m thinking option B (Anomaly detection) can be ruled out quickly—it’s more about spotting unusual data, not categorizing known animals. Option C (Named entity recognition) is for text data, so that’s off. D (Inpainting) is about editing images, so it doesn’t fit either. So even if the question doesn’t say anything about bounding boxes or multiple animals, object detection (A) still seems the most relevant to identify and categorize animals in photos automatically.
It’s A because anomaly detection (B) is for spotting unusual cases, not categorizing known animals. Named entity recognition (C) is text-based, so that’s irrelevant here. Object detection fits perfectly.
A imo, object detection is just the straightforward choice here. It’s specifically built for identifying and classifying objects in images, so it fits perfectly with the goal of categorizing animals without manual tagging. The other options don’t really deal with image classification in this way—anomaly detection looks for unusual patterns, named entity recognition is strictly text-based, and inpainting is about image repair, not recognition.
A imo, object detection is made for automatically spotting and categorizing things in images. That fits best here since anomaly detection is about finding weird stuff, named entity recognition is for text, and inpainting fills missing image parts.