19 citations
- Simon Fraser UniversityCA2 papers
- University of Wollongong in DubaiAE2 papers
- IMC University of Applied Sciences KremsAT1 paper
- Information Technology UniversityPK1 paper
- Institute of Engineering PhysicsRU1 paper
- International Vaccine InstituteKR1 paper
- Mohammed Bin Rashid School of GovernmentAE1 paper
- Murdoch UniversityAU1 paper
- New York University Abu DhabiAE1 paper
- University of LincolnGB1 paper
- University of MalayaMY1 paper
- University of SharjahAE1 paper
12 papers
Prediction of bank transaction fraud using TabNet an adaptive deep learning architecture
Prashanth BS, Manoj Kumar, Ariful Hoque +4
The development of online banking has brought about an increase in fraudulent operations, which is a major problem for banks. This study delves into the urgent requirement for inte…
MixerSENet: A Lightweight Framework for Efficient Hyperspectral Image Classification
Mohammed Q. Alkhatib, Swalpa Kumar Roy, Ali Jamali
In this paper, a novel framework, MixerSENet, is introduced for hyperspectral image (HSI) classification, designed to address the challenges of computational efficiency and limited…
PolSAR Image Classification using a Hybrid Complex-Valued Network (HybridCVNet)
Mohammed Q. Alkhatib
Recently, convolutional neural networks (CNNs) have become popular for image classification due to their effectiveness in computer vision tasks. Now, researchers are exploring the…
Hyperspectral Image Classification using Spectral-Spatial Mixer Network
Mohammed Q. Alkhatib
This paper introduces SS-MixNet, a lightweight and effective deep learning model for hyperspectral image (HSI) classification. The architecture integrates 3D convolutional layers f…
MixerCA: An Efficient and Accurate Model for High-Performance Hyperspectral Image Classification
Mohammed Q. Alkhatib, Ali Jamali
Over the past decade, hyperspectral image (HSI) classification has drawn considerable interest due to HSIs' ability to effectively distinguish terrestrial objects by capturing deta…
ConvVitMamba: Efficient Multiscale Convolution, Transformer, and Mamba-Based Sequence modelling for Hyperspectral Image Classification
Mohammed Q. Alkhatib
Hyperspectral image (HSI) classification remains challenging due to high spectral dimensionality, redundancy, and limited labeled data. Although convolutional neural networks (CNNs…