45 citations · 196 across the 31 of their papers we have counts for
34 papers
Model-Consistent Structured-Hankel Matrix Completion for 3D Sparse Multi-frequency Electromagnetic Source Reconstruction
Shujaat Khan, Abdul Wahab
Reconstruction of 3D electromagnetic currents from sparse, multi-frequency, far-field radiation data is severely ill-posed because sparse sampling masks specific current Fourier mo…
Multi-frequency far-field data enrichment for electromagnetic source reconstruction
Atyab Khalifa Al-Shaqsi, Heba Mohammed Al-Subhi, Xianchao Wang +2
Reconstructing unknown electromagnetic sources from far-field radiation patterns is a fundamental inverse problem with broad applications in biomedical imaging, non-destructive tes…
Approximate Attention Weighting for Sustainable FPGA-Based Vision Transformer Inference
Muhammad Usman, Muhammad Akmal Shafique, Shujaat Khan +1
Vision Transformers have reshaped computer vision by using self-attention to capture global context across image regions. This makes them attractive for edge visual inspection and…
Dynamic Ultrasound Beamforming Using Left-to-Right Arithmetic Adders on FPGA
Muhammad Usman, Shujaat Khan, Dorit Merhof
Adder trees are the computational backbone of delay-and-sum (DAS) ultrasound beamforming, where their implementation directly determines the energy, throughput, and area of a real-…
Blind Ultrasound Image Enhancement via Self-Supervised Physics-Guided Degradation Modeling
Shujaat Khan, Syed Muhammad Atif, Jaeyoung Huh +1
Ultrasound (US) interpretation is hampered by multiplicative speckle, acquisition blur from the point-spread function (PSF), and scanner- and operator-dependent artifacts. Supervis…
Phase Aberration Robust Beamformer for Planewave US Using Self-Supervised Learning
Shujaat Khan, Jaeyoung Huh, Jong Chul Ye
Ultrasound (US) is widely used for clinical imaging applications thanks to its real-time and non-invasive nature. However, its lesion detectability is often limited in many applica…
Tunable Image Quality Control of 3-D Ultrasound using Switchable CycleGAN
Jaeyoung Huh, Shujaat Khan, Sungjin Choi +3
In contrast to 2-D ultrasound (US) for uniaxial plane imaging, a 3-D US imaging system can visualize a volume along three axial planes. This allows for a full view of the anatomy,…
Performance Analysis of Fractional Learning Algorithms
Abdul Wahab, Shujaat Khan, Imran Naseem +1
Fractional learning algorithms are trending in signal processing and adaptive filtering recently. However, it is unclear whether the proclaimed superiority over conventional algori…
A Novel Quantum Calculus-based Complex Least Mean Square Algorithm (q-CLMS)
Alishba Sadiq, Imran Naseem, Shujaat Khan +3
In this research, a novel adaptive filtering algorithm is proposed for complex domain signal processing. The proposed algorithm is based on Wirtinger calculus and is called as q-Co…
GSSMD: A new standardized effect size measure to improve robustness and interpretability in biological applications
Seongyong Park, Shujaat Khan, Muhammad Moinuddin +1
In many biological applications, the primary objective of study is to quantify the magnitude of treatment effect between two groups. Cohens'd or strictly standardized mean differen…
Comments on "Generalization of the gradient method with fractional order gradient direction"
Abdul Wahab, Shujaat Khan
In this paper, a detrimental mathematical mistake is pointed out in the proof of \textit{Theorem 1} presented in the paper\textit{ [Generalization of the gradient method with fract…
Switchable Deep Beamformer
Shujaat Khan, Jaeyoung Huh, Jong Chul Ye
Recent proposals of deep beamformers using deep neural networks have attracted significant attention as computational efficient alternatives to adaptive and compressive beamformers…
Comments on "Design of momentum fractional LMS for Hammerstein nonlinear system identification with application to electrically stimulated muscle model"
Abdul Wahab, Shujaat Khan, Farrukh Zeeshan Khan
The purpose of this article is to discuss some aspects of the convergence analysis performed in the paper [Design of momentum fractional LMS for Hammerstein nonlinear system identi…
AFP-SRC: Identification of Antifreeze Proteins Using Sparse Representation Classifier
Shujaat Khan, Muhammad Usman, Abdul Wahab
Species living in the extreme cold environment fight against the harsh conditions using antifreeze proteins (AFPs), that manipulates the freezing mechanism of water in more than on…
OT-driven Multi-Domain Unsupervised Ultrasound Image Artifact Removal using a Single CNN
Jaeyoung Huh, Shujaat Khan, Jong Chul Ye
Ultrasound imaging (US) often suffers from distinct image artifacts from various sources. Classic approaches for solving these problems are usually model-based iterative approaches…
Multi-Kernel Fusion for RBF Neural Networks
Syed Muhammad Atif, Shujaat Khan, Imran Naseem +2
A simple yet effective architectural design of radial basis function neural networks (RBFNN) makes them amongst the most popular conventional neural networks. The current generatio…
E3-targetPred: Prediction of E3-Target Proteins Using Deep Latent Space Encoding
Seongyong Park, Shujaat Khan, Abdul Wahab
Understanding E3 ligase and target substrate interactions are important for cell biology and therapeutic development. However, experimental identification of E3 target relationship…
Pushing the Limit of Unsupervised Learning for Ultrasound Image Artifact Removal
Shujaat Khan, Jaeyoung Huh, Jong Chul Ye
Ultrasound (US) imaging is a fast and non-invasive imaging modality which is widely used for real-time clinical imaging applications without concerning about radiation hazard. Unfo…
Comments on "A new computing approach for power signal modeling using fractional adaptive algorithms"
Abdul Wahab, Shujaat Khan, Farrukh Zeeshan Khan
In this paper, some points to the convergence analysis performed in the paper [A new computing approach for power signal modeling using fractional adaptive algorithms, ISA Transact…
GSSMD: New metric for robust and interpretable assay quality assessment and hit selection
Seongyong Park, Shujaat Khan
In the high-throughput screening (HTS) campaigns, the Z'-factor and strictly standardized mean difference (SSMD) are commonly used to assess the quality of assays and to select hit…
Chaotic Time Series Prediction using Spatio-Temporal RBF Neural Networks
Alishba Sadiq, Muhammad Sohail Ibrahim, Muhammad Usman +2
Due to the dynamic nature, chaotic time series are difficult predict. In conventional signal processing approaches signals are treated either in time or in space domain only. Spati…
Spatio-Temporal RBF Neural Networks
Shujaat Khan, Jawwad Ahmad, Alishba Sadiq +2
Herein, we propose a spatio-temporal extension of RBFNN for nonlinear system identification problem. The proposed algorithm employs the concept of time-space orthogonality and sepa…
Adaptive and Compressive Beamforming Using Deep Learning for Medical Ultrasound
Shujaat Khan, Jaeyoung Huh, Jong Chul Ye
In ultrasound (US) imaging, various types of adaptive beamforming techniques have been investigated to improve the resolution and contrast-to-noise ratio of the delay and sum (DAS)…
A Novel Adaptive Kernel for the RBF Neural Networks
Shujaat Khan, Imran Naseem, Roberto Togneri +1
In this paper, we propose a novel adaptive kernel for the radial basis function (RBF) neural networks. The proposed kernel adaptively fuses the Euclidean and cosine distance measur…