Research Article
Convolution Neural Network Based Image Classifier
@INPROCEEDINGS{10.4108/eai.27-2-2020.2303205, author={Hussain Qudsia Ejaz and Syed Ali Mehdi}, title={Convolution Neural Network Based Image Classifier}, proceedings={Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India}, publisher={EAI}, proceedings_a={ICIDSSD}, year={2021}, month={3}, keywords={multiple predictions image classification confusion matrix pyramid reduction}, doi={10.4108/eai.27-2-2020.2303205} }- Hussain Qudsia Ejaz
Syed Ali Mehdi
Year: 2021
Convolution Neural Network Based Image Classifier
ICIDSSD
EAI
DOI: 10.4108/eai.27-2-2020.2303205
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.
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