NDLI: A Novel Approach for Image Recognition to Enhance the Quality of Decision Making by Applying Degree of Correlation Using Artificial Neural Networks

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A Novel Approach for Image Recognition to Enhance the Quality of Decision Making by Applying Degree of Correlation Using Artificial Neural Networks

Content Provider	Semantic Scholar
Author	Dara, Raju
Copyright Year	2014
Abstract	Many diversified applications do exist in science & technology, which make use of the primary theory of a recognition phenomenon as one of its solutions. Recognition scenario is incorporated with a set of decisions and the action according to the decision purely relies on the quality of extracted information on utmost applications. Thus, the quality decision making absolutely reckons on processing momentum and precision which are entirely coupled with recognition methodology. In this article, a latest rule is formulated based on the degree of correlation to characterize the generalized recognition constraint and the application is explored with respect to image based information extraction. Machine learning based perception called feed forward architecture of Artificial Neural Network has been applied to attain the expected eminence of elucidation. The proposed method furnishes extraordinary advantages such as less memory requirements, extremely high level security for storing data, exceptional speed and gentle implementation approach.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://www.mecs-press.org/ijigsp/ijigsp-v6-n11/IJIGSP-V6-N11-4.pdf
Language	English
Access Restriction	Open
Subject Keyword	Artificial neural network Computer vision Decision Making High-level programming language Information extraction Machine learning Neural Networks Requirement Solutions
Content Type	Text
Resource Type	Article

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