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Data classification in presence of noise will cause a lot of worse results than expected for pure patterns. In the proposed work we tend to investigate the drawback within the case of deep convolutional neural networks so as to propose solutions which will mitigate influence of noise. The main contributions presented in this proposed work include using convolution neural network as an image classifier for detecting noise in the images and using different opencv2 inbuilt methods to mitigate noise in the images. Though a number of techniques are introduced for this purpose, using neural networks we can achieve a greater accuracy.

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