19 citations · 25 across the 8 of their papers we have counts for
6 papers · 1 filter
Data Leakage in Patch-Based Hyperspectral Image Classification: Quantifying the Impact of Spatial Overlap
Mohammed Q. Alkhatib
Patch-based learning improves hyperspectral image (HSI) classification by exploiting local spectral-spatial information, but random train-test sampling from the same image can caus…
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…
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…
DDF2Pol: A Dual-Domain Feature Fusion Network for PolSAR Image Classification
Mohammed Q. Alkhatib
This paper presents DDF2Pol, a lightweight dual-domain convolutional neural network for PolSAR image classification. The proposed architecture integrates two parallel feature extra…