no code implementations • 26 Oct 2023 • Sania Gul, Muhammad Salman Khan, Muhammad Fazeel
After denoising, the colors of spectrograms are translated to magnitudes of short-time Fourier transform (STFT) using a shallow regression neural network.
1 code implementation • 30 Dec 2022 • Turker Ince, Serkan Kiranyaz, Ozer Can Devecioglu, Muhammad Salman Khan, Muhammad Chowdhury, Moncef Gabbouj
In this study, we propose a novel approach for blind restoration of real-world audio signals by Operational Generative Adversarial Networks (Op-GANs) with temporal and spectral objective metrics to enhance the quality of restored audio signal regardless of the type and severity of each artifact corrupting it.
no code implementations • 10 Aug 2022 • Sania Gul, Muhammad Salman Khan, Syed Waqar Shah
In this paper, we propose a novel approach of binaural dereverberation of a single speech source, using the differences in the interaural cues of the direct path signal and the reverberations.
no code implementations • 9 Aug 2022 • Sania Gul, Muhammad Salman Khan, Syed Waqar Shah, Ata Ur-Rehman
Reverberation results in reduced intelligibility for both normal and hearing-impaired listeners.
no code implementations • 15 Jun 2022 • Tawsifur Rahman, Muhammad E. H. Chowdhury, Amith Khandakar, Zaid Bin Mahbub, Md Sakib Abrar Hossain, Abraham Alhatou, Eynas Abdalla, Sreekumar Muthiyal, Khandaker Farzana Islam, Saad Bin Abul Kashem, Muhammad Salman Khan, Susu M. Zughaier, Maqsud Hossain
This study uses 25 biomarkers and CXR images in predicting the risk in 930 COVID-19 patients admitted during the first wave of COVID-19 (March-June 2020) in Italy.
no code implementations • 24 May 2022 • Muhammad Salman Khan, Adnan Ahmad, Muhammad Humayoun
In this paper, we basically identify different components that we believe are necessary in building an effective automated assessment system in the context of introductory programming courses that involve C/C++ programming.
no code implementations • 26 Mar 2021 • Muhammad Islam, Kaleem Nawaz Khan, Muhammad Salman Khan
To extract liver from medical images is a challenging task due to similar intensity values of liver with adjacent organs, various contrast levels, various noise associated with medical images and irregular shape of liver.
no code implementations • 26 Feb 2021 • Sania Gul, Muhammad Salman Khan, Syed Waqar Shah
In this paper, we formulate a blind source separation (BSS) framework, which allows integrating U-Net based deep learning source separation network with probabilistic spatial machine learning expectation maximization (EM) algorithm for separating speech in reverberant conditions.
no code implementations • 15 Dec 2020 • Kaleem Nawaz Khan, Faiq Ahmad Khan, Anam Abid, Tamer Olmez, Zumray Dokur, Amith Khandakar, Muhammad E. H. Chowdhury, Muhammad Salman Khan
Finally, the third study shows a precision of 98. 29% on the noisy PASCAL dataset with transfer learning approach.
no code implementations • 25 Nov 2020 • Tawsifur Rahman, Amith Khandakar, Yazan Qiblawey, Anas Tahir, Serkan Kiranyaz, Saad Bin Abul Kashem, Mohammad Tariqul Islam, Somaya Al Maadeed, Susu M Zughaier, Muhammad Salman Khan, Muhammad E. H. Chowdhury
The accuracy, precision, sensitivity, f1-score, and specificity in the detection of COVID-19 with gamma correction on CXR images were 96. 29%, 96. 28%, 96. 29%, 96. 28% and 96. 27% respectively.
1 code implementation • 29 Mar 2020 • Muhammad E. H. Chowdhury, Tawsifur Rahman, Amith Khandakar, Rashid Mazhar, Muhammad Abdul Kadir, Zaid Bin Mahbub, Khandaker Reajul Islam, Muhammad Salman Khan, Atif Iqbal, Nasser Al-Emadi, Mamun Bin Ibne Reaz, T. I. Islam
The networks were trained to classify two different schemes: i) normal and COVID-19 pneumonia; ii) normal, viral and COVID-19 pneumonia with and without image augmentation.