40 citations · 97 across the 5 of their papers we have counts for
5 papers
UNEM: UNrolled Generalized EM for Transductive Few-Shot Learning
Long Zhou, Fereshteh Shakeri, Aymen Sadraoui +3
Transductive few-shot learning has recently triggered wide attention in computer vision. Yet, current methods introduce key hyper-parameters, which control the prediction statistic…
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…
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…
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…