13 citations · 23 across the 8 of their papers we have counts for
8 papers
Retinal Vessel Segmentation via a Multi-resolution Contextual Network and Adversarial Learning
Tariq M. Khan, Syed S. Naqvi, Antonio Robles-Kelly +1
Timely and affordable computer-aided diagnosis of retinal diseases is pivotal in precluding blindness. Accurate retinal vessel segmentation plays an important role in disease progr…
MESAHA-Net: Multi-Encoders based Self-Adaptive Hard Attention Network with Maximum Intensity Projections for Lung Nodule Segmentation in CT Scan
Muhammad Usman, Azka Rehman, Abd Ur Rehman +5
Accurate lung nodule segmentation is crucial for early-stage lung cancer diagnosis, as it can substantially enhance patient survival rates. Computed tomography (CT) images are wide…
MKIS-Net: A Light-Weight Multi-Kernel Network for Medical Image Segmentation
Tariq M. Khan, Muhammad Arsalan, Antonio Robles-Kelly +1
Image segmentation is an important task in medical imaging. It constitutes the backbone of a wide variety of clinical diagnostic methods, treatments, and computer-aided surgeries.…
Neural Network Compression by Joint Sparsity Promotion and Redundancy Reduction
Tariq M. Khan, Syed S. Naqvi, Antonio Robles-Kelly +1
Compression of convolutional neural network models has recently been dominated by pruning approaches. A class of previous works focuses solely on pruning the unimportant filters to…
A Residual Encoder-Decoder Network for Segmentation of Retinal Image-Based Exudates in Diabetic Retinopathy Screening
Malik A. Manan, Tariq M. Khan, Ahsan Saadat +2
Diabetic retinopathy refers to the pathology of the retina induced by diabetes and is one of the leading causes of preventable blindness in the world. Early detection of diabetic r…
RC-Net: A Convolutional Neural Network for Retinal Vessel Segmentation
Tariq M Khan, Antonio Robles-Kelly, Syed S. Naqvi
Over recent years, increasingly complex approaches based on sophisticated convolutional neural network architectures have been slowly pushing performance on well-established benchm…
Leveraging Image Complexity in Macro-Level Neural Network Design for Medical Image Segmentation
Tariq M. Khan, Syed S. Naqvi, Erik Meijering
Recent progress in encoder-decoder neural network architecture design has led to significant performance improvements in a wide range of medical image segmentation tasks. However,…
A Derivative-free Method for Quantum Perceptron Training in Multi-layered Neural Networks
Tariq M. Khan, Antonio Robles-Kelly
In this paper, we present a gradient-free approach for training multi-layered neural networks based upon quantum perceptrons. Here, we depart from the classical perceptron and the…