Convolution Neural Network Based Image Classifier

Ejaz, Hussain Qudsia and Mehdi, Syed Ali (2021) Convolution Neural Network Based Image Classifier. In: ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India.

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Abstract

The concept of Deep Learning is emanated in machine learning as an enhanced research area and is empirical to various image applications. The objective of the project propounded in the paper, is applying the abstract of an algorithm of Deep Learning, viz, Convolutional neural networks (CNN) for multiple image classification. The algorithm is assessed on variegated datasets, which consist 2399 images taken from google, myntra fashion clothes, etc. The algorithm’s performance is gauged based on the quality metric known as Confusion Matrix. The analysis is done and the model successfully classifies each image using VGG19 model of CNN.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: multiple predictions image classification confusion matrix pyramid reduction
Subjects: T Technology > T Technology (General)
Depositing User: EAI Editor IV
Date Deposited: 06 May 2021 09:36
Last Modified: 06 May 2021 09:36
URI: https://eprints.eudl.eu/id/eprint/2909

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