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    Persian handwritten digit recognition by random forest and convolutional neural networks

    , Article 9th Iranian Conference on Machine Vision and Image Processing,18 November 2015 through 19 November 2015 ; Volume 2016-February , 2015 , Pages 37-40 ; 21666776 (ISSN) ; 9781467385398 (ISBN) Zamani, Y ; Souri, Y ; Rashidi, H ; Kasaei, S ; Sharif University of Technology
    IEEE Computer Society 
    Abstract
    Persian handwritten digit recognition has attracted some interests in the research community by introduction of large Hoda dataset. In this paper, the well-known random forest (RF) and convolutional neural network (CNN) algorithms are investigated for Persian handwritten digit recognition on the Hoda dataset. Using the Hoda dataset as a standard testbed, we have performed some experiments with different preprocessing steps, feature types, and baselines. It is then shown that RFs and CNNs perform competitively with the state-of-the-art methods on this dataset, while CNNs being the fastest if appropriate hardware is available