International Scientific Journal of Engineering and Management

An International Scholarly || Multidisciplinary || Open Access || Indexing in all major Database & Metadata
ISSN: 2583-6129

Impact Factor: 6.674

ACCESSING THE STRENGTH OF CRYPTOGRAPHY USING MACHINE LEARNING MODELS

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ACCESSING THE STRENGTH OF CRYPTOGRAPHY USING MACHINE LEARNING MODELS

Balasubramani V.S, Monishkumar S, Rahul S, Mr.R.Mohanabharathi(AP/CSE)

 CSE & Selvam College of Technology

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Abstract -       Standard procedures for picture recuperation are not maintained for the predictably expansive picture informational collection. These disservices can be taken out by involving things in the image for picture retrieval. This sort of picture recuperation is called as Cheerful Based Picture Recuperation (CBIR).D-Channel is works with CBIR is locked in around the visual features like shape, assortment and surface. The Thickness Scale Invariant Part Change (D-Channel) is a stand separated among the most locally incorporate finder and descriptors which is utilized as a piece of the majority of the vision programming. We focus texture, color, shape, size, string based picture planning with better accuracy. These features integrate Surface, Assortment, Shape and Region. It is a hot assessment district and researchers have made various techniques to use these component for exact recuperation of required pictures from the data bases. In this work we present a composing investigation of the Substance Based Picture Recuperation (CBIR) procedures considering Surface, Assortment, Shape and Region. We moreover review a piece of the top tier contraptions created for CBIR


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