Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Recognition of Handwritten Digit using Convolutional Neural Network in
  Python with Tensorflow and Comparison of Performance for Various Hidden
  Layers   In recent times, with the increase of Artificial Neural Network (ANN), deep
learning has brought a dramatic twist in the field of machine learning by
making it more artificially intelligent. Deep learning is remarkably used in
vast ranges of fields because of its diverse range of applications such as
surveillance, health, medicine, sports, robotics, drones, etc. In deep
learning, Convolutional Neural Network (CNN) is at the center of spectacular
advances that mixes Artificial Neural Network (ANN) and up to date deep
learning strategies. It has been used broadly in pattern recognition, sentence
classification, speech recognition, face recognition, text categorization,
document analysis, scene, and handwritten digit recognition. The goal of this
paper is to observe the variation of accuracies of CNN to classify handwritten
digits using various numbers of hidden layers and epochs and to make the
comparison between the accuracies. For this performance evaluation of CNN, we
performed our experiment using Modified National Institute of Standards and
Technology (MNIST) dataset. Further, the network is trained using stochastic
gradient descent and the backpropagation algorithm.

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The categories of this paper are: alg-geom
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The categories of this paper are: bayes-an
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The categories of this paper are: stat
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The categories of this paper are: cond-mat
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The categories of this paper are: acc-phys
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The categories of this paper are: math-ph
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The categories of this paper are: plasm-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: hep-lat
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The categories of this paper are: gr-qc
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The categories of this paper are: chao-dyn
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The categories of this paper are: hep-th
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The categories of this paper are: quant-ph
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The categories of this paper are: math
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The categories of this paper are: astro-ph