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@article{170816,
        author = {AATHISHASAN S and GUGAN M and KAVIN S and KAWIN M},
        title = {DIGITAL SIGNATURE USING NEURAL NETWORK},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {7},
        pages = {1743-1746},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=170816},
        abstract = {Digital  signatures serve as the main means of authorization and  authentication in legal transactions, there is a greater need for effective automated solutions for signature verification [1].In contrast to identification information like a password, PIN, PKI, or key cards that may be misplaced, stolen, or exchanged, the handwritten signature's captured values are specific to each person and nearly impossible to replicate. Verification of  signatures is intuitive and natural. The technology is  trustworthy and simple to understand. The fact that signatures are already widely recognized as the standard technique for identity verification is the main advantage that signature verification systems have over other kinds of technologies [2].},
        keywords = {},
        month = {December},
        }