What is Pattern Recognition

1.

Feature-based algorithms for prediction and pattern recognition purposes. Learn more in: Computer Science in Sport

2.

It means the procedure of finding a certain series of signals in a longer data file or signal stream. Learn more in: Pattern-Based Identification in P2P Systems

3.

A machine learning process which identifies the pattern of physical systems using data belong to investigated systems. Learn more in: General Perspectives on Electromyography Signal Features and Classifiers Used for Control of Human Arm Prosthetics

4.

The assignment of some sort of output value to a given input value, according to some specific algorithm; the technologies designed to provide a reasonable answer for all possible inputs Learn more in: Technological Approaches to Maintaining Academic Integrity in Management Education

5.

Pattern recognition is the process of classifying input data into objects or classes based on key features. Learn more in: Expertise Development for Next-Generation Digital Learners

6.

Process of classifying patterns according to common features. Feature extraction is therefore an ultimate prerequisite for the process of pattern recognition. Learn more in: In Machina Systems for the Rational De Novo Peptide Design

7.

A science that focuses in finding regularities in data. Learn more in: A Hybrid Intelligent Risk Identification Model for Configuration Management in Aerospace Systems

8.

The act of taking in raw data and taking an action based on the category of the data. It is a field within the area of machine learning. Learn more in: Data Mining: Payoffs and Pitfalls

9.

The task of assigning each input value to one of a given set of classes (for example, to infer whether a given pixel is a natural or man-made object). Learn more in: Conditional Random Fields for Modeling Structured Data

10.

Part of machine learning (with supervised learning underpinnings) that classifies or extracts patterns from raw data (measurements or observations) relying on the features of the data. Learn more in: Linguistic Indexing of Images with Database Mediation

11.

A branch of machine learning that deals with identification of regularities and patterns in a given data. Learn more in: Computational Methods for Prediction of Protein-Protein Interactions: PPI Prediction Methods

12.

Discovering or detecting the explicit relation or repetitive structures in a dataset using data science. Learn more in: Demand Forecasting Models With Time Series and Random Forest

13.

An important area of research concerned to discover or identify automatically figures, characters, shapes, forms, and patterns without active human participation in the decision process. It is also related with classify data in categories. Classification consists in learning a model for separating the data categories, that kind of machine learning can be approached using statistical (parametric or no-parametric models) or heuristic techniques. If some prior information is given in learning process, it is called supervised or semi-supervised, else it is called unsupervised. Learn more in: Automatic Classification of Impact-Echo Spectra I

14.

Pattern recognition is the scientific discipline whose goal is the classification of objects into a number of categories or classes. Objects can be, for example, signal waveforms or any type of measurement that needs to be classified. These objects are here referred to using the generic term “patterns.” Learn more in: Unobtrusive Movement Interaction for Mobile Devices

15.

Analytical approaches that detect trends, sequences, or relationships within a dataset. Learn more in: Approaches to Detect Securities Fraud in Capital Markets

16.

Techniques to identify a given pattern from a heterogamous corpus. This pattern could be in any media. Learn more in: Crime Profiling System

17.

Finding patterns in the small parts of a problem helps us see how it all fits together. Learn more in: Preparing Pre-Service Teachers for the Future: Computational Thinking as a Scaffold for Critical Thinking

18.

The automatic detection of regularities in data using algorithms and the corresponding use of these regularities to perform actions. Learn more in: Integrated Continuous Healthcare Team Computer System Architecture

19.

The act of taking in raw data and taking an action based on the category of the data. It is a field within the area of machine learning. Learn more in: Data Mining Fundamental Concepts and Critical Issues

20.

Research area that enclose the development of methods and automatized techniques for identification and classification of samples in specific groups, in accordance with representative characteristics. Learn more in: Artificial Intelligence in Computer-Aided Diagnosis

21.

The act of taking in raw data and taking an action based on the category of the data. It is a field within the area of machine learning. Learn more in: Applications of Data Mining in the Healthcare Industry

22.

It means the procedure of finding a certain series of signals in a longer data file or signal stream. Learn more in: A Content-Sensitive Approach to Search in Shared File Storages

23.

A branch of machine learning that recognizes and separates the patterns of one class from the other. Learn more in: Soft-Computational Techniques and Spectro-Temporal Features for Telephonic Speech Recognition: An Overview and Review of Current State of the Art

24.

Pattern Recognition in the discipline which tries to find the classes in the datasets of the various applications and it is the major building block of artificially intelligent systems. Learn more in: Support Vector Machines and Applications

25.

A sub-topic of machine learning, which aims to classify input patterns into a specific class of pre-defined groups. The classification is usually based on the availability of a set of patterns that have already been classified. Therefore, the resulting learning strategy is based on supervised learning Learn more in: Hierarchical Neuro-Fuzzy Systems Part I

26.

Automatic process of extracting, representing, and splitting conspicuous characteristics from a dataset to produce several subsets that can be associated with concepts normally accepted by humans. Learn more in: New Perspectives of Pattern Recognition for Automatic Credit Card Fraud Detection

27.

The procedure of finding a certain series of signals in a longer data file or signal stream. Learn more in: Light-Weight Content-Based Search for File Sharing Systems

28.

A machine learning process which identifies the pattern of physical systems using data belong to investigated systems. Learn more in: General Perspectives on Electromyography Signal Features and Classifiers Used for Control of Human Arm Prosthetics

29.

Pattern recognition is the automated recognition of patterns and regularities in data. Pattern recognition is closely related to artificial intelligence and machine learning, together with applications such as data mining and knowledge discovery in databases, and is often used interchangeably with these terms. Learn more in: Guidance Algorithm for Unmanned Aerial Vehicles on a Basis System of Technical Viewing

30.

Procedure of finding a certain series of signals in a longer data file or signal stream. Learn more in: Content-Based Searching in Group Communication Systems

31.

The ability to see something and realize what it is and where it belongs. Humans are extremely adept at this and various forms of this are now computer processes. Learn more in: Advanced Methodologies Descriptions and Applications

32.

A branch of machine learning that focuses on the recognition of patterns and regularities in data; in some cases, considered to be nearly synonymous with machine learning. Learn more in: A Comparative Study of Machine Learning Techniques for Gesture Recognition Using Kinect

33.

Concerned with the classification of individual patterns into pre-specified classes (i.e., supervised pattern recognition), or with the identification and characterization of pattern classes (i.e., unsupervised pattern recognition). Learn more in: Image Classification and Retrieval with Mining Technologies