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Pattern recognition is the task of assigning a class to an observation based on patterns extracted from data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess (PR) capabilities but their primary function is to distinguish and create emergent patterns.
In computer science, pattern matching is the act of checking a given sequence of tokens for the presence of the constituents of some pattern. In contrast to pattern recognition , the match usually has to be exact: "either it will or will not be a match."
An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.
Pattern recognition – branch of machine learning that examines how machines recognize regularities in data. As with machine learning, teachers can train machines to recognize patterns by providing them with example inputs and outputs (i.e. Supervised Learning ), or the machines can recognize patterns without being trained on any example ...
Elliot Bruce Koffman (born 7 May 1942 in Boston, Massachusetts) [1] is a noted computer scientist and educationist.He is the author of numerous widely used introductory textbooks for more than 10 [2] different programming languages, including Ada, BASIC, C, C++, FORTRAN, Java, Modula-2, and Pascal.
Probably the most commercially important recent object-oriented languages are Java, developed by Sun Microsystems, as well as C# and Visual Basic.NET (VB.NET), both designed for Microsoft's .NET platform. Each of these two frameworks shows, in its way, the benefit of using OOP by creating an abstraction from implementation.
Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different view points, in many different sizes and scales or even when they are translated or rotated.
There are two basic types of core OCR algorithm, which may produce a ranked list of candidate characters. [23] Matrix matching involves comparing an image to a stored glyph on a pixel-by-pixel basis; it is also known as pattern matching, pattern recognition, or image correlation. This relies on the input glyph being correctly isolated from the ...