29 citations · 32 across the 8 of their papers we have counts for
9 papers · 1 filter
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…
D-PerceptCT: Deep Perceptual Enhancement for Low-Dose CT Images
Taifour Yousra Nabila, Azeddine Beghdadi, Marie Luong +3
Low Dose Computed Tomography (LDCT) is widely used as an imaging solution to aid diagnosis and other clinical tasks. However, this comes at the price of a deterioration in image qu…
A New Lightweight Hybrid Graph Convolutional Neural Network -- CNN Scheme for Scene Classification using Object Detection Inference
Ayman Beghdadi, Azeddine Beghdadi, Mohib Ullah +2
Scene understanding plays an important role in several high-level computer vision applications, such as autonomous vehicles, intelligent video surveillance, or robotics. However, t…
CD-COCO: A Versatile Complex Distorted COCO Database for Scene-Context-Aware Computer Vision
Ayman Beghdadi, Azeddine Beghdadi, Malik Mallem +2
The recent development of deep learning methods applied to vision has enabled their increasing integration into real-world applications to perform complex Computer Vision (CV) task…
Kalman Filter Based Multiple Person Head Tracking
Mohib Ullah, Maqsood Mahmud, Habib Ullah +3
For multi-target tracking, target representation plays a crucial rule in performance. State-of-the-art approaches rely on the deep learning-based visual representation that gives a…
Adaptive Context Encoding Module for Semantic Segmentation
Congcong Wang, Faouzi Alaya Cheikh, Azeddine Beghdadi +1
The object sizes in images are diverse, therefore, capturing multiple scale context information is essential for semantic segmentation. Existing context aggregation methods such as…