Search for: souri--y
0.012 seconds

    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 
    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