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A modern definition of pattern recognition is: The field of pattern recognition is concerned with the automatic discovery of regularities in data through the use of computer algorithms and with the use of these regularities to take actions such as classifying the data into different categories.
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.
Neural networks help make soft computing extraordinarily flexible and capable of handling high-level problems. In soft computing, neural networks aid in pattern recognition, predictive modeling, and data analysis. They are also used in image recognition, natural language processing, speech recognition, and systems. [3] [10]
Neuromorphic computing is an approach ... implemented with memristors that have applications in high level pattern recognition ... Wetware computer; Zeroth (software) ...
Software design pattern, a standard form for a solution to common problems in software design. Architectural pattern, for software architecture; Interaction design pattern, used in interaction design / human-computer interaction; Pattern recognition, in machine learning; In machine learning, a non-null finite sequence of constant and variable ...
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."
In computer vision, 3D object recognition involves recognizing and determining 3D information, such as the pose, volume, or shape, of user-chosen 3D objects in a photograph or range scan. Typically, an example of the object to be recognized is presented to a vision system in a controlled environment, and then for an arbitrary input such as a ...
A very common type of prior knowledge in pattern recognition is the invariance of the class (or the output of the classifier) to a transformation of the input pattern. This type of knowledge is referred to as transformation-invariance. The mostly used transformations used in image recognition are: translation; rotation; skewing; scaling.