We've got 61 shorthands for pattern recognition »
Acronyms that contain the term pattern recognition
What does pattern recognition mean? This page is about the various possible meanings of the acronym, abbreviation, shorthand or slang term: pattern recognition.
| Term | Definition | Rating |
|---|---|---|
| PRS | Pattern Recognition Signals | |
| CPR | Candlesticks Pattern Recognition | |
| PRASA | Pattern Recognition Association of South Africa | |
| GMPR | Geometric Modelling and Pattern Recognition | |
| IUPR | Image Understanding and Pattern Recognition | |
| PRADA | Pattern Recognition, Abstraction, Decomposition, and Algorithms | |
| PRR | Pattern Recognition Receptors | |
| CVPR | Computer Vision and Pattern Recognition | |
| PRIP | Pattern Recognition and Image Processing | |
| ICPR | International Conference on Pattern Recognition | |
| CVPR | IEEE Conference on Computer Vision and Pattern Recognition | |
| PRIB | Pattern Recognition in Bioinformatics | |
| PRT | Pattern Recognition Toolbox | |
| SPPRA | Signal Processing Pattern Recognition and Applications | |
| PRMU | Pattern Recognition and Media Understanding | |
| SPQR | System for Pattern Query and Recognition | |
| DDPR | Depth Depending Pattern Recognition | |
| PRL | Pattern Recognition Letters | |
| AAPR | Austrian Association for Pattern Recognition | |
| FBPR | Feature Based Pattern Recognition | |
| PRAS | Pattern Recognition Analytical Service | |
| BSPRA | Backward Screening Pattern Recognition Algorithm | |
| PIPR | Pose Invariant Pattern Recognition | |
| RRPR | Reproducible Research in Pattern Recognition | |
| RRPR | Reproducible Research on Pattern Recognition | |
| PRIP | Pattern Recognition and Information Processing | |
| PPRS | Pakistan Pattern Recognition Society | |
| PRADA | Pattern Recognition Abstraction Decomposition and Algorithms | |
| PRR | Pattern Recognition Receptory | |
| TSPR | Traffic sign pattern recognition | |
| PRADA | Pattern Recognition Abstraction Decomposition And a | |
| IAPR | International Association of Pattern Recognition | |
| CPRL | Compact Pattern Recognition Language | |
| SPRS | Slovenian Pattern Recognition Society | |
| ACPR | Asian Conference on Pattern Recognition | |
| PRR | Pattern Recognition Receptor | |
| IAPR | International Association of Pattern Recognition | |
| MVPR | Machine Vision and Pattern Recognition | |
| INAPR | Indonesian Association for Pattern Recognition | |
| PRS | Pattern Recognition System | |
| PRIME | Pattern Recognition Informatics and Medical Engineering | |
| ICPR | International Conference on Pattern Recognition | |
| DPR | Digital Pattern Recognition | |
| CVPR | Computer Vision and Pattern Recognition | |
| CVPL | Computer Vision Pattern Recognition and Machine Learning | |
| APRP | Adaptive Pattern Recognition Process | |
| OLPARS | On-Line Pattern Analysis & Recognition System | |
| INAPR | Indonesian Association for Pattern Recognition | |
| NOBIM | Norwegian Society for Image Processing and Pattern Recognition | |
| FIDAC | Film Input to Digital Automatic Computer and associated syntax-directed pattern recognition programming system | |
| FIDAC | Film Input to Digital Automatic Computer and associated syntax-directed pattern recognition programming system | |
| FIDAC | Film Input to Digital Automatic Computer and associated syntax-directed pattern recognition programming system | |
| FIDAC | Film Input to Digital Automatic Computer and associated syntax-directed pattern recognition programming system | |
| BMVA | British Machine Vision Association and Society for Pattern Recognition | |
| OAGM | Austrian Association for Pattern Recognition | |
| IAPR | International Association for Pattern Recognition | |
| APRS | Australian Pattern Recognition Society | |
| IAPR | International Association for Pattern Recognition | |
| IAPR | International Association for Pattern Recognition | |
| IPRCS | Irish Pattern Recognition and Classification Society | |
| SSPR | Structural and Syntactic Pattern Recognition |
What does pattern recognition mean?
- Pattern recognition
- Pattern recognition is the automated recognition of patterns and regularities in data. It has applications in statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Pattern recognition has its origins in statistics and engineering; some modern approaches to pattern recognition include the use of machine learning, due to the increased availability of big data and a new abundance of processing power. These activities can be viewed as two facets of the same field of application, and they have undergone substantial development over the past few decades. Pattern recognition systems are commonly trained from labeled "training" data. When no labeled data are available, other algorithms can be used to discover previously unknown patterns. KDD and data mining have a larger focus on unsupervised methods and stronger connection to business use. Pattern recognition focuses more on the signal and also takes acquisition and signal processing into consideration. It originated in engineering, and the term is popular in the context of computer vision: a leading computer vision conference is named Conference on Computer Vision and Pattern Recognition. In machine learning, pattern recognition is the assignment of a label to a given input value. In statistics, discriminant analysis was introduced for this same purpose in 1936. An example of pattern recognition is classification, which attempts to assign each input value to one of a given set of classes (for example, determine whether a given email is "spam"). Pattern recognition is a more general problem that encompasses other types of output as well. Other examples are regression, which assigns a real-valued output to each input; sequence labeling, which assigns a class to each member of a sequence of values (for example, part of speech tagging, which assigns a part of speech to each word in an input sentence); and parsing, which assigns a parse tree to an input sentence, describing the syntactic structure of the sentence.Pattern recognition algorithms generally aim to provide a reasonable answer for all possible inputs and to perform "most likely" matching of the inputs, taking into account their statistical variation. This is opposed to pattern matching algorithms, which look for exact matches in the input with pre-existing patterns. A common example of a pattern-matching algorithm is regular expression matching, which looks for patterns of a given sort in textual data and is included in the search capabilities of many text editors and word processors.
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"pattern recognition." Abbreviations.com. STANDS4 LLC, 2024. Web. 3 May 2024. <https://www.abbreviations.com/pattern%20recognition>.
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