2026 Ismail Ben Ayed: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	50	5646	5486	215	204	251	9269

Overview

Ismail Ben Ayed is affiliated with the École de Technologie Supérieure in Canada and has contributed extensively to the field of computer science, particularly focusing on artificial intelligence and its applications in medical imaging and related domains. Their research spans multiple subfields including artificial intelligence, computer vision and pattern recognition, radiology, nuclear medicine and imaging, computational mechanics, and biomedical engineering.

The scientist's publication record includes work on various topics such as:

Domain Adaptation and Few-Shot Learning
Advanced Neural Network Applications
AI in cancer detection
Medical Image Segmentation Techniques
Multimodal Machine Learning Applications
Digital Imaging for Blood Diseases
COVID-19 diagnosis using AI

Ismail Ben Ayed has collaborated frequently with several researchers, including:

José Dolz
Éric Granger
Christian Desrosiers
Julio Silva-Rodríguez
Malik Boudiaf

Their research has been published in numerous venues, with a particular emphasis on:

arXiv (Cornell University)
Medical Image Analysis
Lecture Notes in Computer Science
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Scientific Reports

Among recent notable publications are:

Boundary loss for highly unbalanced segmentation, 2020, Medical Image Analysis
Parameter-free Online Test-time Adaptation, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
State-of-the-art retinal vessel segmentation with minimalistic models, 2022, Scientific Reports
Source-free domain adaptation for image segmentation, 2022, Medical Image Analysis
Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images via Max-Min Uncertainty, 2021, IEEE Transactions on Medical Imaging

Best Publications

Boundary loss for highly unbalanced segmentation.

Hoel Kervadec;Jihene Bouchtiba;Christian Desrosiers;Eric Granger

638
Citations
HyperDense-Net: A Hyper-Densely Connected CNN for Multi-Modal Image Segmentation

Jose Dolz;Karthik Gopinath;Jing Yuan;Herve Lombaert

496
Citations
3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study.

Jose Dolz;Christian Desrosiers;Ismail Ben Ayed

464
Citations
Constrained-CNN losses for weakly supervised segmentation.

Hoel Kervadec;Jose Dolz;Meng Tang;Eric Granger

294
Citations
On Regularized Losses for Weakly-supervised CNN Segmentation

Meng Tang;Federico Perazzi;Abdelaziz Djelouah;Ismail Ben Ayed

284
Citations
Multiregion Image Segmentation by Parametric Kernel Graph Cuts

M B Salah;A Mitiche;I B Ayed

276
Citations
Multiregion level-set partitioning of synthetic aperture radar images

I.B. Ayed;A. Mitiche;Z. Belhadj

272
Citations
Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses

Jerome Rony;Luiz G. Hafemann;Luiz S. Oliveira;Ismail Ben Ayed

261
Citations
Right ventricle segmentation from cardiac MRI: a collation study.

Caroline Petitjean;Maria A. Zuluaga;Wenjia Bai;Jean Nicolas Dacher

254
Citations
Benchmark on Automatic Six-Month-Old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge

Li Wang;Dong Nie;Guannan Li;Elodie Puybareau

198
Citations
Variational and Level Set Methods in Image Segmentation

Amar Mitiche;Ismail Ben Ayed

194
Citations
Annotation-efficient deep learning for automatic medical image segmentation

Shanshan Wang;Cheng Li;Rongpin Wang;Zaiyi Liu

180
Citations
Parameter-free Online Test-time Adaptation

Unknown

163
Citations
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?

Malik Boudiaf;Hoel Kervadec;Ziko Imtiaz Masud;Pablo Piantanida

153
Citations
Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation

Jose Dolz;Christian Desrosiers;Li Wang;Jing Yuan

133
Citations
Deep Clustering: On the Link Between Discriminative Models and K-Means

Mohammed Jabi;Marco Pedersoli;Amar Mitiche;Ismail Ben Ayed

118
Citations
Dense Multi-path U-Net for Ischemic Stroke Lesion Segmentation in Multiple Image Modalities

Jose Dolz;Ismail Ben Ayed;Christian Desrosiers

114
Citations
Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images

Aaron Carass;Jennifer L. Cuzzocreo;Shuo Han;Carlos R. Hernandez-Castillo

114
Citations
Polarimetric image segmentation via maximum-likelihood approximation and efficient multiphase level-sets

I. Ben Ayed;A. Mitiche;Z. Belhadj

113
Citations
Source-Free Domain Adaptation for Image Segmentation

Unknown

112
Citations
Embedding Overlap Priors in Variational Left Ventricle Tracking

I. Ben Ayed;Shuo Li;I. Ross

102
Citations
Effective Level Set Image Segmentation With a Kernel Induced Data Term

M. Ben Salah;A. Mitiche;I. Ben Ayed

97
Citations
A Unifying Mutual Information View of Metric Learning: Cross-Entropy vs. Pairwise Losses

Malik Boudiaf;Jérôme Rony;Imtiaz Masud Ziko;Eric Granger

89
Citations

Frequent Co-Authors

Eric Granger École de Technologie Supérieure

Shuo Li Case Western Reserve University

Christian Desrosiers École de Technologie Supérieure

Amar Mitiche Institut National de la Recherche Scientifique

Yuri Boykov University of Waterloo

Terry M. Peters University of Western Ontario

Dinggang Shen ShanghaiTech University

Aaron Fenster University of Western Ontario

Andrea Lodi Cornell University

Martin Rajchl Imperial College London

External Links

Personal website of Ismail Ben Ayed Google Scholar page

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