000 | 02950nam a22004575i 4500 | ||
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001 | 978-1-4471-2188-6 | ||
003 | DE-He213 | ||
005 | 20170628033620.0 | ||
007 | cr nn 008mamaa | ||
008 | 110906s2011 xxk| s |||| 0|eng d | ||
020 |
_a9781447121886 _9978-1-4471-2188-6 |
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024 | 7 |
_a10.1007/978-1-4471-2188-6 _2doi |
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050 | 4 | _aQ337.5 | |
050 | 4 | _aTK7882.P3 | |
072 | 7 |
_aUYQP _2bicssc |
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072 | 7 |
_aCOM016000 _2bisacsh |
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082 | 0 | 4 |
_a006.4 _223 |
100 | 1 |
_aPlötz, Thomas. _eauthor. |
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245 | 1 | 0 |
_aMarkov Models for Handwriting Recognition _h[electronic resource] / _cby Thomas Plötz, Gernot A. Fink. |
264 | 1 |
_aLondon : _bSpringer London, _c2011. |
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300 |
_aVI, 78p. 5 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aSpringerBriefs in Computer Science, _x2191-5768 |
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505 | 0 | _aIntroduction -- General Architecture -- Markov Model Concepts: The Essence -- Markov Model Based Handwriting Recognition -- Recognition Systems for Practical Applications -- Discussion. | |
520 | _aSince their first inception more than half a century ago, automatic reading systems have evolved substantially, thereby showing impressive performance on machine-printed text. The recognition of handwriting can, however, still be considered an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, so far, no standard procedures for building Markov-model-based recognizers could be established though trends toward unified approaches can be identified. Markov Models for Handwriting Recognition provides a comprehensive overview of the application of Markov models in the research field of handwriting recognition, covering both the widely used hidden Markov models and the less complex Markov-chain or n-gram models. First, the text introduces the typical architecture of a Markov model-based handwriting recognition system, and familiarizes the reader with the essential theoretical concepts behind Markovian models. Then, the text gives a thorough review of the solutions proposed in the literature for open problems in applying Markov model-based approaches to automatic handwriting recognition. | ||
650 | 0 | _aComputer science. | |
650 | 0 | _aOptical pattern recognition. | |
650 | 1 | 4 | _aComputer Science. |
650 | 2 | 4 | _aPattern Recognition. |
700 | 1 |
_aFink, Gernot A. _eauthor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9781447121879 |
830 | 0 |
_aSpringerBriefs in Computer Science, _x2191-5768 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-1-4471-2188-6 |
912 | _aZDB-2-SCS | ||
999 |
_c16020 _d16020 |