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Hello mplemesos1954,
Thank you for raising this and for sharing your reasoning. We appreciate the effort you put into your feedback.
However, after reviewing the question, the current answer set remains correct. Here’s a brief explanation for the two matches you’ve flagged:
• Computer vision → pattern recognition
While it’s true that Computer vision is used in object detection, its core and foundational capability is pattern recognition, identifying visual patterns such as shapes, edges, textures, and faces in images or video. Pattern recognition is the broader underlying function that powers all Computer vision tasks.
• Classification → object detection
Object detection is a two-step process: it first locates an object within an image, then classifies it (e.g., a car, person, or dog). The classification step, assigning a label to a detected region, is what connects this scenario to the Classification workload type. Your spam/not-spam example is a great illustration of classification, and the same labeling logic applies when identifying detected objects.
We do acknowledge that this question can feel counterintuitive, especially since object detection is commonly associated with Computer vision in broader AI discussions. We will review the explanation to ensure this nuance is communicated more clearly so future learners are not confused.
We truly appreciate your feedback; it helps us improve the quality and clarity of our content.
Kind regards,
Irene @ Tutorials Dojo
