Multi-banknote Identification Using a Single Neural Network

@inproceedings{Khashman2005MultibanknoteIU,
  title={Multi-banknote Identification Using a Single Neural Network},
  author={Adnan Khashman and Boran Sekeroglu},
  booktitle={ACIVS},
  year={2005}
}
Real-life applications of neural networks require a high degree of success, usability and reliability. Image processing has an importance for both data preparation and human vision to increase the success and reliability of pattern recognition applications. The combination of both image processing and neural networks can provide sufficient and robust solutions to problems where intelligent recognition is required. This paper presents an implementation of neural networks for the recognition of… CONTINUE READING

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Key Quantitative Results

  • An overall recognition ratio of 95% for the single network is considered sufficient considering the reduction in time cost.

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Citations

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Banknote Recognition in Real Time Using ANN

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CITES BACKGROUND & METHODS

Intelligent coin identification system

  • 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control
  • 2006
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CITES METHODS

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