Feature fusion of fruit image categorization using machine learning

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Fatima Shameem; Seshashayee M.

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Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF NONLINEAR ANALYSIS AND APPLICATIONS Year:2022 | Volume:13 | Issue:Special Issue for selected papers of ICDACT Page(s): 71-76

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Information Journal Paper

Title

Feature fusion of fruit image categorization using machine learning

Author(s)

Fatima Shameem | Seshashayee M. | Issue Writer Certificate

Keywords

Fruit Classification

Feature Fusion

feature extraction

Multiclass SVM

Abstract

Fruit Categorization is a classification problem that the agricultural fruit industry needs to solve in order to reduce the post-harvesting losses that occur during the traditional system of manual grading. Fruit grading which involves categorization is an important step in obtaining high fruit quality and market demand. There are various feature selection challenges in agriculture produced especially fruit grading to build an appropriate machine learning approach to solve the problem of reducing losses. In this paper, we describe different features, a machine learning technique that has been recently applied to different Fruit Classification problems producing a promising result. We discuss the feature extraction method, technique used in image classification applications for fruit prediction. A proposed multiclass Fruit Classification model is theoretically described and their most distinguishing features and technique is then presented at the end of this paper.

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