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Cloud-based efficient scheme for handwritten digit recognition

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Abstract

Handwritten character recognition has been acknowledged and achieved more prominent attention in pattern recognition research community due to enormous applications & vagueness in application methods, while cloud computing delivers appropriate, on-demand access of network to a joint tarn of configurable computing resource & digital devices. Principally two steps, feature extraction & character recognition, are required for Handwritten Digit Recognition (HDR), which are primarily based on some classification algorithms. Previous studies show the nonexistence of higher precision and truncated computational swiftness for HDR procedure. “The projected research aimed to make the trail towards digitalization clearer by providing high accuracy and faster cloud-based computational for handwritten digits recognition. The current study utilized a cloud-based neural network (CNN) as a classifier, suitable parameters of dataset MNIST for testing and training purposes as a framework called DL4J for cloud-based handwritten digit recognition. The said system magnificently managed to obtained precision up to 99.41%, which is higher than previously projected systems. Additionally, the proposed method decreases cost and computational time significantly as using cloud-based architecture for testing and training; as a result, the algorithm becomes more efficient.

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Authors and Affiliations

  1. Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China

    Zeeshan Shaukat, Saqib Ali, Chuangbai Xiao & Sana Sahiba

  2. Faculty of Life Science & Bioengineering, Beijing University of Technology, Beijing, 100124, China

    Qurat ul Ain Farooq

  3. Division of Science & Technology, University of Education, Lahore, 54000, Pakistan

    Allah Ditta

Authors
  1. Zeeshan Shaukat
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  2. Saqib Ali
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  3. Qurat ul Ain Farooq
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  4. Chuangbai Xiao
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  5. Sana Sahiba
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  6. Allah Ditta
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Correspondence to Zeeshan Shaukat.

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Highlights

• Cloud-Based Handwritten Character Recognition System.

• Cloud Based Novel Neural Network

• 99.41% Accuracy Obtained, Decreases in Cost & Computational time

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Shaukat, Z., Ali, S., Farooq, Q.u.A. et al. Cloud-based efficient scheme for handwritten digit recognition. Multimed Tools Appl 79, 29537–29549 (2020). https://doi.org/10.1007/s11042-020-09494-1

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  • DOI: https://doi.org/10.1007/s11042-020-09494-1

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