A Lightweight Visual Font Style Recognition With Quantized Convolutional Autoencoder

Article Properties
  • DOI (url)
    10.1109/ojcs.2024.3378709
  • Publication Date
    2024/01/01
  • Journal
    IEEE Open Journal of the Computer Society
  • Indian UGC (journal)
  • Refrences
    31
  • Moshiur Rahman Tonmoy Advanced Machine Intelligence Research Lab, Dhaka, Bangladesh ORCID (unauthenticated)
  • Abdul Fattah Rakib Department of Computer Science and Engineering, University of Asia Pacific, Dhaka, Bangladesh ORCID (unauthenticated)
  • Rashik Rahman Department of Computer Science and Engineering, University of Asia Pacific, Dhaka, Bangladesh ORCID (unauthenticated)
  • Md. Akhtaruzzaman Adnan Department of Computer Science and Engineering, University of Asia Pacific, Dhaka, Bangladesh ORCID (unauthenticated)
  • M. F. Mridha Department of Computer Science, American International University-Bangladesh, Dhaka, Bangladesh ORCID (unauthenticated)
  • Jie Huang School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan
  • Jungpil Shin School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan ORCID (unauthenticated)
Cite
Tonmoy, Moshiur Rahman, et al. “A Lightweight Visual Font Style Recognition With Quantized Convolutional Autoencoder”. IEEE Open Journal of the Computer Society, vol. 5, 2024, pp. 120-3, https://doi.org/10.1109/ojcs.2024.3378709.
Tonmoy, M. R., Rakib, A. F., Rahman, R., Adnan, M. A., Mridha, M. F., Huang, J., & Shin, J. (2024). A Lightweight Visual Font Style Recognition With Quantized Convolutional Autoencoder. IEEE Open Journal of the Computer Society, 5, 120-130. https://doi.org/10.1109/ojcs.2024.3378709
Tonmoy MR, Rakib AF, Rahman R, Adnan MA, Mridha MF, Huang J, et al. A Lightweight Visual Font Style Recognition With Quantized Convolutional Autoencoder. IEEE Open Journal of the Computer Society. 2024;5:120-3.
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Refrences
Title Journal Journal Categories Citations Publication Date
Capsule Network on Font Style Classification

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