AI Learning Center

Understand face comparison before you trust a score

Practical LooksCompare guides about visual similarity, family resemblance, photo quality, score interpretation, privacy and responsible testing.

How does AI face comparison work?

How facial information becomes a numerical representation used for visual comparison.

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Which photos give the best results?

Lighting, angle, sharpness and face position can significantly affect an estimate.

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How reliable is an AI similarity score?

What a percentage can tell you — and what it cannot prove.

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Face similarity vs face recognition

Why resemblance scoring and identity recognition are different tasks.

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Why do similarity scores change?

How lighting, pose, lens perspective and expression can move a result.

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Common face comparison mistakes

Photo and interpretation mistakes that most often confuse results.

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Family resemblance explained

Why a child can resemble both parents in different traits and at different ages.

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Which parent does a child look like more?

How an AI mom-vs-dad comparison works and how to interpret close scores.

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Comparing children's faces responsibly

Privacy, permission and responsible interpretation when children's photos are involved.

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How age changes face similarity

Why growth and aging can change a visual comparison over time.

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Same faces, different photos

A practical experiment showing how photo choice alone can move a similarity result.

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What does a 70% similarity score mean?

Why a precise-looking percentage is not genetic relatedness or identity probability.

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10 parent-child comparison factors

Ten variables that can change what a family resemblance comparison sees.

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Baby vs older child resemblance

Why resemblance to mom or dad can appear to change as a child grows.

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How to test a face comparison tool

A repeatable method for checking stability without chasing a preferred result.

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