Excel International Journal of Technology, Engineering & Management

ISSN : (Print): 2348–0378 |
(Online): 2349–8455

2.5

CiteScore

8.8

Global Impact Factor

Unique Label Natural Object Classification Using Artificial Neural Network

Paper ID: EIJTEM_2016_3_3_49-51

Author's Name: E. Deepan Kumar, V. Surendhiran, N. Naveen and S.S. Karthik Kumar

Volume: 3

Issue: 3

Year: 2016

Page No: 49-51

Abstract:

Supervised machine learning algorithms used to identify and classify the unique label natural image with great success. Multi object identification, in that image may be fall into different categories, in a highly irregular pattern making problem. It very hard to diagnose them and within each class all the images are dissimilar from one another. It is a ubiquitous problem in data analysis. However, identification of multi label instances is typically more lengthy or expensive to process and compare with single-label instances. This approach for used learning has been widely studied on reducing labeling effort for single-label problems, current research on multi-label learning remains in a preliminary state. In this paper we propose an approach for artificial neural network for unique label natural image classification.

Keywords: Artificial Neural Network,Feature Extraction, Discrete Wavelet Transform

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