Boosting Image classification using Refined Feature Extraction-A Case study of Image Classification

Document Type : Primary Research paper

Authors

1 Research Scholar, Bishop Heber College, Trichchirappalli -17.

2 Assitant Professor, Bishop Heber College, Trichirappalli-17 (Affiliated to Bharathidasan University), Trichirappalli, Tamilnadu.

Abstract

In real life large amount of data are collect and understand not possible. Here feature extraction helps to reduce the amount of data without losing any important or relevant information. This paper survey on pre-processing, feature extraction for deep convolution neural network, support vector machine classifier. Feature extraction is the process of transforming image data pixel into binary or real value. Feature extraction involves identifying and extracting features based on applications. A designated convolutional neural network feature extraction algorithm extracts most significant features by the first layer of a convolutional neural network or layers of network. Finally, the challenges in convolutional neural network for future extraction research re discussed.
Keywords: Feature extract, patch match, convolutional neural network, support vector machine classifier.
Int. J. of Aquatic Science
Volume 12, Issue 2 - Serial Number 2
June 2021
Pages 3321-3327

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