Siamese Network
Definition
A siamese network compares inputs with parallel branches and shared weights.
An architecture with two or more branches that share the same weights and generate representations for comparison or similarity.
Simply explained
Two things are viewed with the same scale so that their similarity can be comparably assessed.
Why it matters in practice
The term helps to select, develop, evaluate AI systems in a well-founded manner and realistically assess their technical risks.
Example from business
Two product images are processed by identical encoders and their embeddings compared.
Limits and pitfalls
- Forgetting weight sharing, poorly selecting negative pairs, or not calibrating similarity thresholds.
Origin & history
Bromley and co-authors described Siamese networks in 1993 for signature verification.
Use in mid-sized companies
- Possible example: Two product images are processed by identical encoders and their embeddings compared.
Frequently asked questions
What does Siamese neural network mean?
An architecture with two or more branches that share the same weights and generate representations for comparison or similarity. What mistakes should be avoided? Forgetting weight sharing, poorly selecting negative pairs, or not calibrating similarity thresholds.
Sources
Source checked on 10.10.2026. Editorial application examples are hypothetical; no evidence of real customer results.
Editorially reviewed on: