Contribution to K-Nearest neighbour’s system for under water mine classification

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

This paper review mine detection and classification using high resolution images of the seafloor and under water mine by K-Nearest Neighbors algorithm the k-Nearest Neighbors algorithm (or k-NN for short) is a non-parametric method used for detection and classification In both cases, the input consists of the k closest training examples in the attribute space. The result depends on whether k-NN is used for detection or classification: e contributions concentrate on feature selection and object classification. the mine classification provide different method like Sophisticated Filter Method, Ensemble Learning, Automatic Target Recognition (ATR), Composite Relevance measure (CRM) , Semester-Shafer theory but these method are not clear classification in mine according to the object. Recent researchers are focus on the better classification according to the object information by K-Nearest Neighbors (K-NN).

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Keywords

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