40 citations · 113 across the 13 of their papers we have counts for
13 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…
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…
Deep Learning for Multi-Label Learning: A Comprehensive Survey
Adane Nega Tarekegn, Mohib Ullah, Faouzi Alaya Cheikh
Multi-label learning is a rapidly growing research area that aims to predict multiple labels from a single input data point. In the era of big data, tasks involving multi-label cla…
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…
A Neural Network based Framework for Effective Laparoscopic Video Quality Assessment
Zohaib Amjad Khan, Azeddine Beghdadi, Mounir Kaaniche +2
Video quality assessment is a challenging problem having a critical significance in the context of medical imaging. For instance, in laparoscopic surgery, the acquired video data s…
Residual Networks based Distortion Classification and Ranking for Laparoscopic Image Quality Assessment
Zohaib Amjad Khan, Azeddine Beghdadi, Mounir Kaaniche +1
Laparoscopic images and videos are often affected by different types of distortion like noise, smoke, blur and nonuniform illumination. Automatic detection of these distortions, fo…
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…
Towards a Video Quality Assessment based Framework for Enhancement of Laparoscopic Videos
Zohaib Amjad Khan, Azeddine Beghdadi, Faouzi Alaya Cheikh +6
Laparoscopic videos can be affected by different distortions which may impact the performance of surgery and introduce surgical errors. In this work, we propose a framework for aut…
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…
Generative Smoke Removal
Oleksii Sidorov, Congcong Wang, Faouzi Alaya Cheikh
In minimally invasive surgery, the use of tissue dissection tools causes smoke, which inevitably degrades the image quality. This could reduce the visibility of the operation field…
Can Image Enhancement be Beneficial to Find Smoke Images in Laparoscopic Surgery?
Congcong Wang, Vivek Sharma, Yu Fan +4
Laparoscopic surgery has a limited field of view. Laser ablation in a laproscopic surgery causes smoke, which inevitably influences the surgeon's visibility. Therefore, it is of vi…
A Smoke Removal Method for Laparoscopic Images
Congcong Wang, Faouzi Alaya Cheikh, Mounir Kaaniche +1
In laparoscopic surgery, image quality can be severely degraded by surgical smoke, which not only introduces error for the image processing (used in image guided surgery), but also…