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What are common mistakes to avoid with Object Detection

Intermediate

Answer

A common mistake with Object Detection is applying it without fully understanding the underlying data or problem, which often leads to weak or misleading results. Skipping proper testing before relying on it in a real project is another frequent error.
Real-world example A self checkout system uses object detection to identify and count multiple grocery items placed on a scanner at once.

Common follow-ups: What is Computer Vision, How is Object Detection evaluated in practice, What tools are commonly used for Object Detection