3 citations · 3 across the 2 of their papers we have counts for
8 papers
Augmenting Generative Adversarial Networks for Speech Emotion Recognition
Siddique Latif, Muhammad Asim, Rajib Rana +3
Generative adversarial networks (GANs) have shown potential in learning emotional attributes and generating new data samples. However, their performance is usually hindered by the…
Advanced kNN: A Mature Machine Learning Series
Muhammad Asim, Muaaz Zakria
k-nearest neighbour (kNN) is one of the most prominent, simple and basic algorithm used in machine learning and data mining. However, kNN has limited prediction ability, i.e., kNN…
Adversarial Machine Learning Attack on Modulation Classification
Muhammad Usama, Muhammad Asim, Junaid Qadir +2
Modulation classification is an important component of cognitive self-driving networks. Recently many ML-based modulation classification methods have been proposed. We have evaluat…
Blind Image Deconvolution using Pretrained Generative Priors
Muhammad Asim, Fahad Shamshad, Ali Ahmed
This paper proposes a novel approach to regularize the ill-posed blind image deconvolution (blind image deblurring) problem using deep generative networks. We employ two separate d…
Motion Corrected Multishot MRI Reconstruction Using Generative Networks with Sensitivity Encoding
Muhammad Usman, Muhammad Umar Farooq, Siddique Latif +2
Multishot Magnetic Resonance Imaging (MRI) is a promising imaging modality that can produce a high-resolution image with relatively less data acquisition time. The downside of mult…
Leveraging Deep Stein's Unbiased Risk Estimator for Unsupervised X-ray Denoising
Fahad Shamshad, Muhammad Awais, Muhammad Asim +3
Among the plethora of techniques devised to curb the prevalence of noise in medical images, deep learning based approaches have shown the most promise. However, one critical limita…