2 citations · 3 across the 6 of their papers we have counts for
7 papers
CT-DegradBench: A Physics-Informed Benchmark for CT Degradation Detection and Severity Estimation
Yousra Nabila Taifour, Marouane Tliba, Zuheng Ming +9
Computed tomography (CT) images are frequently degraded by acquisition artifacts, including noise, blur, streaking, aliasing, and metal artifacts. Yet CT enhancement is still large…
Morphology-Aware KOA Classification: Integrating Graph Priors with Vision Models
Marouane Tliba, Mohamed Amine Kerkouri, Yassine Nasser +4
Knee osteoarthritis (KOA) diagnosis from radiographs remains challenging due to the subtle morphological details that standard deep learning models struggle to capture effectively.…
Modeling Beyond MOS: Quality Assessment Models Must Integrate Context, Reasoning, and Multimodality
Mohamed Amine Kerkouri, Marouane Tliba, Aladine Chetouani +2
This position paper argues that Mean Opinion Score (MOS), while historically foundational, is no longer sufficient as the sole supervisory signal for multimedia quality assessment…
Applications of Knowledge Distillation in Remote Sensing: A Survey
Yassine Himeur, Nour Aburaed, Omar Elharrouss +4
With the ever-growing complexity of models in the field of remote sensing (RS), there is an increasing demand for solutions that balance model accuracy with computational efficienc…
SDF2Net: Shallow to Deep Feature Fusion Network for PolSAR Image Classification
Mohammed Q. Alkhatib, M. Sami Zitouni, Mina Al-Saad +2
Polarimetric synthetic aperture radar (PolSAR) images encompass valuable information that can facilitate extensive land cover interpretation and generate diverse output products. E…
Attention based Dual-Branch Complex Feature Fusion Network for Hyperspectral Image Classification
Mohammed Q. Alkhatib, Mina Al-Saad, Nour Aburaed +2
This research work presents a novel dual-branch model for hyperspectral image classification that combines two streams: one for processing standard hyperspectral patches using Real…
Operational Neural Networks for Parameter-Efficient Hyperspectral Single-Image Super-Resolution
Alexander Ulrichsen, Paul Murray, Stephen Marshall +4
Hyperspectral Imaging is a crucial tool in remote sensing which captures far more spectral information than standard color images. However, the increase in spectral information com…