In recent years, huge amounts of data in form of images has been efficiently created and accumulated at extraordinary rates. This huge amount of data that has high volume and velocity has presented us with the problem of coming up with practical and effective ways to classify it for analysis. Existing classification systems can never fulfil the demand and the difficulties of accurately classifying such data. In this paper, we built a Convolutional Neural Network (CNN) which is one of the most powerful and popular machine learning tools used in image recognition systems for classifying images from one of the widely used image datasets CIFAR-10. This paper also gives a thorough overview of the working of our CNN architecture with its parameters and difficulties.
CITATION STYLE
Kumar, P., & Rawat, S. (2019). Implementing Convolutional Neural Networks for Simple Image Classification. International Journal of Engineering and Advanced Technology, 9(2), 3616–3619. https://doi.org/10.35940/ijeat.b3279.129219
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