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Signature recognition using machine learning

Signatures are frequently used as a form of verification and personal identification. Numerous credentials, including bank checks and legal documents, require signature confirmation. It takes a lot of time and effort to verify the signature on a lot of documents. As a result, systems for biometric personal verification and authentication that depend on distinctive, quantifiable physical traits (such as fingerprints, handprints, faces, iris scans, or DNA scans) or behavioural traits have experienced accelerated growth (gait, sound, etc.). The capability of the recommended system to distinguish real signatures from forgeries is described using a variety of ways. Using two datasets to train a siamese network on, this method introduces a new strategy for signature verification and identification. final year project is based on IEEE Paper.this will be one of the best Final year engineering project for computer science. Components that we will provide are.
1.complete documentation support
2.complete working hardware/software implemented in students environment
3.classes will held accordingly.

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