9 Grammatical Pitfalls

pattern recognition

noun, Computers.
the automated identification of shapes or forms or patterns of speech. Unabridged
Based on the Random House Dictionary, © Random House, Inc. 2015.
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Examples from the web for pattern recognition
  • pattern recognition seems to me to be dependent on your focus.
  • pattern recognition is essential to survival, so this is no surprise.
  • It think this topic stretches deeper than a simple pattern recognition mechanism gone awry.
  • At its core, the medical model is pattern recognition.
  • There's interesting work on the effect of mood on pattern recognition that might link up nicely.
  • Such pattern recognition is thought to be a component of language acquisition.
  • The blocks are designed to function as an educational tool to facilitate spatial reasoning and pattern recognition.
  • It's an exercise in pattern recognition that is sure to delight.
  • Such pattern recognition is thought to be a component of language acquisition.
  • Visual pattern recognition software is a rapidly developing field that has already produced significant results.
pattern recognition in Technology
artificial intelligence, data processing
A branch of artificial intelligence concerned with the classification or description of observations.
Pattern recognition aims to classify data (patterns) based on either a priori knowledge or on statistical information extracted from the patterns. The patterns to be classified are usually groups of measurements or observations, defining points in an appropriate multidimensional space.
A complete pattern recognition system consists of a sensor that gathers the observations to be classified or described; a feature extraction mechanism that computes numeric or symbolic information from the observations; and a classification or description scheme that does the actual job of classifying or describing observations, relying on the extracted features.
The classification or description scheme is usually based on the availability of a set of patterns that have already been classified or described. This set of patterns is termed the training set and the resulting learning strategy is characterised as supervised. Learning can also be unsupervised, in the sense that the system is not given an a priori labelling of patterns, instead it establishes the classes itself based on the statistical regularities of the patterns.
The classification or description scheme usually uses one of the following approaches: statistical (or decision theoretic), syntactic (or structural), or neural. Statistical pattern recognition is based on statistical characterisations of patterns, assuming that the patterns are generated by a probabilistic system. Structural pattern recognition is based on the structural interrelationships of features. Neural pattern recognition employs the neural computing paradigm that has emerged with neural networks.
The Free On-line Dictionary of Computing, © Denis Howe 2010
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