Neural networks are used for pattern recognition in various industries, including communications, medicine, business, entertainment, and law enforcement. These networks mimic biological neurons and can recognize speech, handwriting, faces, and disease symptoms. They can also analyze financial trends and create intelligent opponents in video games. In law enforcement, they can be used to detect explosives.
There are several uses of neural networks for pattern recognition involving a fairly wide range of industries. Much of this type of work is done in recognition in communications, such as speech recognition and handwriting recognition, although it can also be used to recognize faces. Recognizing patterns can also be important for medical and business fields, where such software can be used to diagnose disease and analyze financial statistics. There are also applications for using neural networks for pattern recognition in the fields of electronic entertainment and law enforcement.
The use of neural networks for pattern recognition has become quite popular in recent decades, as computer technology has advanced enough to adapt to such networks. Artificial or synthetic neural networks are a type of artificial intelligence program designed to mimic or replicate the way biological neurons in the human central nervous system receive and process information. One of the best applications many researchers have found for this technology is the use of neural networks for pattern recognition.
Some of the more common uses of neural networks for pattern recognition are in speech and handwriting recognition. A number of different software programs use speech recognition, such as talk-to-text programs and software used for automated telephone systems. There are also handwriting programs that can analyze written content and then transform that handwriting into typed text. Such programs can also be used to analyze and recognize speech patterns, handwriting and faces from images and audio files loaded into a computer, which can be used to identify individuals based on these samples.
There are also notable applications in medicine and business. Neural networks can be used to “learn” the common symptoms of various diseases and then recognize those symptoms as models for diagnosing patients. Similarly, you can analyze patterns in economic and financial trends to make predictions about stock performance or future earnings potential. Some financial uses of neural networks for pattern recognition may also include analyzing information on loan or credit extension applications.
Electronic entertainment, such as gaming software, can also use neural networks for pattern recognition. This is often done to create more realistic or intelligent opponents in video games, and is particularly useful for games such as chess where pattern recognition can often tell the best move for a computer opponent to make. Pattern recognition may also be important for use in law enforcement, such as the development of electronic “noses” that can “sniff out” explosives. These devices “learn” to identify traces of particles associated with different types of explosives and can therefore recognize their presence in a package or baggage.
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