Publications

For more updated lists of publications, you can visit my Google Scholar.

Pre-Prints

  1. Adam, T., Malyshev, A., Hassan, M. F., Mohamed, N. S., & Salam, M. S. H. (2023). Accelerated Proximal Iterative re-Weighted $\ell_1 $ Alternating Minimization for Image Deblurring. arXiv preprint arXiv:2309.05204. (Codes)
  2. Adam, T. (2024). Manifold Quadratic Penalty Alternating Minimization for Sparse Principal Component Analysis. arXiv preprint arXiv:2411.06654.

Journal Papers

  1. Yin, M., Adam, T., Paramesran, R., Hassan, M. F. (2024). An ℓ0 total generalized variation for impulse noise removal. Multimedia Tools and Applications.
  2. Hassan, M. F., Adam, T., Rajagopal, H., & Paramesran, R. (2022). A hue preserving uniform illumination image enhancement via triangle similarity criterion in HSI color space. The Visual Computer, 1-12.
  3. Hassan, M. F., Adam, T., Yin, M., & Paramesran, R. (2023). Effect of image denoising on geometric moments in image applications. The Journal of Analysis, 31(3), 1783-1803.
  4. Adam, T., Paramesran, R., & Ratnavelu, K. (2022). A combined higher order non-convex total variation with overlapping group sparsity for Poisson noise removal. Computational and Applied Mathematics, 41(4), 1-33.
  5. Yin, M., Adam, T., Paramesran, R., & Hassan, M. F. (2022). An ℓ0-overlapping group sparse total variation for impulse noise image restoration. Signal Processing: Image Communication, 102, 116620. (MATLAB Codes)
  6. Adam, T., Paramesran, R., Mingming, Y., & Ratnavelu, K. (2021). Combined higher order non-convex total variation with overlapping group sparsity for impulse noise removal. Multimedia Tools and Applications, 80(12), 18503-18530.
  7. Adam, T., & Paramesran, R. (2020). Hybrid non-convex second-order total variation with applications to non-blind image deblurring. Signal, Image and Video Processing, 14(1), 115-123.
  8. Adam, T., & Paramesran, R. (2019). Image denoising using combined higher order non-convex total variation with overlapping group sparsity. Multidimensional Systems and Signal Processing, 30(1), 503-527.
  9. Adam, T. B., Salam, M. S., & Gunawan, T. S. (2013). Wavelet cesptral coefficients for isolated speech recognition. Indonesian Journal of Electrical Engineering and Computer Science, 11(5), 2731-2738.
  10. Adam, T. B., & Salam, M. (2012). Spoken english alphabet recognition with mel frequency cepstral coefficients and back propagation neural networks. International Journal of Computer Applications, 42(12), 21-27.

Conference Papers

  1. Hassan, M. F., Adam, T., & Paramesran, R. (2023, June). Lightness enhancement method for low illumination night-time image. In AIP Conference Proceedings (Vol. 2756, No. 1). AIP Publishing.
  2. Adam, T., Hassan, M. F., & Paramesran, R. (2021, September). A Study on Staircase Artifacts in Total Variation Image Restoration. In 2021 IEEE International Conference on Signal and Image Processing Applications (ICSIPA) (pp. 83-88). IEEE. (MATLAB Codes)
  3. Adam, T. B., Salam, M. S., & Gunawan, T. S. (2013, October). Wavelet based Cepstral Coefficients for neural network speech recognition. In 2013 IEEE International Conference on Signal and Image Processing Applications (pp. 447-451). IEEE.

Book Chapters

  1. Adam, T., Mohamed, N. S.,Hassan, M. F., & Paramesran, R. (2022). The alternating direction method of multipliers (ADMM) for large-scale convex optimization problems: Applications in image and signal processing. In Operations Research & Analytics in Practice: Theory, Methods & Applications . UTeM Press & MSORSM (Accepted).