Dynamic Signature Verification System Based On One Real Signature

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@article{1701175,
      author = {Ambica Gupta, Aakriti Rai, A. Pravallika, B. SathyaBama},
      title = {Dynamic Signature Verification System Based On One Real Signature },
      journal = {Iconic Research And Engineering Journals},
      year = {2019},
      volume = {2},
      number = {10},
      pages = {140-143},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1701175.pdf},
      abstract = {This paper is based on dynamic signature used for image processing and biometric traits. Signature verification is essential in preventing duplication of documents in numerous financial, legal and other commercial fields. The project presents several unique and complicated difficulties: high/low intra-class variability (an individual?s signature may vary from day-to-day), large temporal variation (signature may vary completely over time), and high/low inter-class similarity (original signature should be different from one another). To build a signature, we need a signature verification system using a Neural Network (NN). Our paper focuses on building systems trained on data with varying degrees of information, as well as experimenting with different objective functions to obtain optimal error rates.},
      keywords = {Signature verification, bio-metric trait, Neural network (NN)},
      month = {April},
  }