43 citations · 49 across the 9 of their papers we have counts for
10 papers
Learning Discriminative Representations for Multi-Label Image Recognition
Mohammed Hassanin, Ibrahim Radwan, Salman Khan +1
Multi-label recognition is a fundamental, and yet is a challenging task in computer vision. Recently, deep learning models have achieved great progress towards learning discriminat…
Mitigating the Impact of Adversarial Attacks in Very Deep Networks
Mohammed Hassanin, Ibrahim Radwan, Nour Moustafa +2
Deep Neural Network (DNN) models have vulnerabilities related to security concerns, with attackers usually employing complex hacking techniques to expose their structures. Data poi…
A Deep Marginal-Contrastive Defense against Adversarial Attacks on 1D Models
Mohammed Hassanin, Nour Moustafa, Murat Tahtali
Deep learning algorithms have been recently targeted by attackers due to their vulnerability. Several research studies have been conducted to address this issue and build more robu…
Elimination of Central Artefacts of L-SPECT with Modular Partial Ring Detectors by Shifting Center of Scanning
Manu Francis, Murat Tahtali, Mark R Pickering
The Lightfield Single Photon Emission Computed Tomography (L-SPECT) system is developed to overcome some of the drawbacks in conventional SPECT by applying the idea of plenoptic im…
Uncertainty Analysis in 3D SPECT Reconstruction based on Probabilistic Programming
Manu Francis, Muhammed Tarek, Mark Pickering +1
Single Photon Emission Computed Tomography (SPECT) is one of the nuclear medicine imaging modalities used for functional analysis of animal and human organs. Gamma rays emitted fro…
Visual Affordance and Function Understanding: A Survey
Mohammed Hassanin, Salman Khan, Murat Tahtali
Nowadays, robots are dominating the manufacturing, entertainment and healthcare industries. Robot vision aims to equip robots with the ability to discover information, understand i…
Adaptive Adjustment of Relaxation Parameters for Algebraic Reconstruction Technique and its Possible Application to Sparsity Prior X-ray CT Reconstruction
Sajib Saha, Murat Tahtali, Andrew Lambert +1
In this paper, we systematically evaluate the performance of adaptive adjustment of the relaxation parameters of various iterative algorithms for X-ray CT reconstruction relying on…
Evaluating the Performance of BSBL Methodology for EEG Source Localization On a Realistic Head Model
Sajib Saha, Rajib Rana, Ya. I. Nesterets +3
Source localization in EEG represents a high dimensional inverse problem, which is severely ill-posed by nature. Fortunately, sparsity constraints have come into rescue as it helps…
Sparse Bayesian Learning for EEG Source Localization
Sajib Saha, Frank de Hoog, Ya. I. Nesterets +3
Purpose: Localizing the sources of electrical activity from electroencephalographic (EEG) data has gained considerable attention over the last few years. In this paper, we propose…
CT Reconstruction from Simultaneous Projections: A Step towards Capturing CT in One Go
Sajib Saha, Murat Tahtali, Andrew Lambert +1
This paper focuses on minimizing the time requirement for CT capture through innovative simultaneous x-ray capture method. The state-of-the-art CT imaging methodology captures a se…