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  2. Pattern recognition - Wikipedia

    en.wikipedia.org/wiki/Pattern_recognition

    [9] [10] The last two examples form the subtopic image analysis of pattern recognition that deals with digital images as input to pattern recognition systems. [11] [12] Optical character recognition is an example of the application of a pattern classifier. The method of signing one's name was captured with stylus and overlay starting in 1990.

  3. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    Optical Recognition of Handwritten Digits Dataset Normalized bitmaps of handwritten data. Size normalized and mapped to bitmaps. 5620 Images, text Handwriting recognition, classification 1998 [147] E. Alpaydin et al. Pen-Based Recognition of Handwritten Digits Dataset Handwritten digits on electronic pen-tablet.

  4. Local binary patterns - Wikipedia

    en.wikipedia.org/wiki/Local_binary_patterns

    This idea is motivated by the fact that some binary patterns occur more commonly in texture images than others. A local binary pattern is called uniform if the binary pattern contains at most two 0-1 or 1-0 transitions. For example, 00010000 (2 transitions) is a uniform pattern, but 01010100 (6 transitions) is not.

  5. Syntactic pattern recognition - Wikipedia

    en.wikipedia.org/wiki/Syntactic_pattern_recognition

    Syntactic pattern recognition can be used instead of statistical pattern recognition if clear structure exists in the patterns. One way to present such structure is via strings of symbols from a formal language. In this case, the differences in the structures of the classes are encoded as different grammars.

  6. Feature (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Feature_(machine_learning)

    In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a data set. [1] Choosing informative, discriminating, and independent features is crucial to produce effective algorithms for pattern recognition, classification, and regression tasks.

  7. Neuromorphic computing - Wikipedia

    en.wikipedia.org/wiki/Neuromorphic_computing

    For example, a neuromemristive system may replace the details of a cortical microcircuit's behavior with an abstract neural network model. [49] There exist several neuron inspired threshold logic functions [9] implemented with memristors that have applications in high level pattern recognition applications.

  8. Adaptive resonance theory - Wikipedia

    en.wikipedia.org/wiki/Adaptive_resonance_theory

    Adaptive resonance theory (ART) is a theory developed by Stephen Grossberg and Gail Carpenter on aspects of how the brain processes information.It describes a number of artificial neural network models which use supervised and unsupervised learning methods, and address problems such as pattern recognition and prediction.

  9. Conference on Computer Vision and Pattern Recognition

    en.wikipedia.org/wiki/Conference_on_Computer...

    The Pattern Analysis and Machine Intelligence Young Researcher Award is an award given by the Technical Committee on Pattern Analysis and Machine Intelligence of the IEEE Computer Society to a researcher within 7 years of completing their Ph.D. for outstanding early career research contributions.