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  • (Noisy) fingerprint classification  (1)
  • Rough sets  (1)
  • 1
    Electronic Resource
    Electronic Resource
    Rough knowledge-based network, fuzziness and classification (1998)
    Springer
    Neural computing & applications 7 (1998), S. 17-25 
    Details
    ISSN: 1433-3058
    Keywords: Classification ; Fuzzy MLP ; Knowledge-based networks ; Rough sets
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract A method of integrating rough sets and fuzzy multilayer perceptron (MLP) for designing a knowledge-based network for pattern recognition problems is described. Rough set theory is used to extract crude knowledge from the input domain in the form of rules. The syntax of these rules automatically determines the optimal number of hidden nodes while the dependency factors are used in the initial weight encoding. Results on classification of speech data demonstrate the superiority of the system over the fuzzy and conventional versions of the MLP.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01413706
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    Noisy fingerprints classification with directional FFT based features using MLP (1998)
    Springer
    Neural computing & applications 7 (1998), S. 180-191 
    Details
    ISSN: 1433-3058
    Keywords: Fast Fourier Transform (FFT) ; Multilayer Perceptron (MLP) ; (Noisy) fingerprint classification
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract A methodology is described for classifying noisy fingerprints directly from raw unprocessed images. The directional properties of fingerprints are exploited as input features by computing one-dimensional fast Fourier transform (FFT) of the images over some selected bands in four and eight directions. The ability of the multilayer perceptron (MLP) for generating complex boundaries is utilised for the purpose of classification. The superiority of the method over some existing ones is established for fingerprints corrupted with various types of distortions, especially random noise.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01414169
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    Paper (German National Licenses)
    Fulltext
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