CV
PhD researcher in machine learning and computer vision, Poitiers & Gjøvik.
Education
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2023 – 2026
PhD in Computer Science (cotutelle)
University of Poitiers, France · NTNU, Norway
- Perceptual quality assessment for augmented reality.
- Advisors: Prof. Mohamed-Chaker Larabi and Prof. Seyed Ali Amirshahi.
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until 2022
Engineering studies in Computer Science
Specialisation in machine learning and computer vision
Research
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2023 – present
Doctoral researcher
XLIM, University of Poitiers · Colourlab, NTNU Gjøvik
- Subjective and objective quality assessment for augmented reality, including the ARIQA-3DS stereoscopic dataset and its 36-participant HMD study.
- Blind image quality metrics built on efficient transformer architectures.
- Cross-laboratory experimental design and reproducible evaluation pipelines.
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2022 – 2024
Medical imaging AI — collaborative projects
With Université d'Orléans (PRISME) and partners
- Knee osteoarthritis severity grading from radiographs with Swin Transformers.
- Domain adaptation and localisation-aware modelling for clinical computer vision.
Research interests
- Blind / no-reference image quality assessment
- Augmented and mixed reality visual experience modelling
- Transformer architectures and distillation for perceptual AI
- Medical image analysis and trustworthy computer vision
Publications
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When Restoration Becomes the Reference: Reusing Full-Reference IQA in Blind Settings
conference IEEE International Conference on Image Processing (ICIP)
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ARIQA-3DS: A Stereoscopic Image Quality Assessment Dataset for Realistic Augmented Reality
dataset arXiv preprint · 5th Workshop on Computer Vision for Multimedia Spatial Intelligence
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Enhancing Content Representation for AR Image Quality Assessment Using Knowledge Distillation
journal IEEE Transactions on Circuits and Systems for Video Technology
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TransformAR: A Light-Weight Transformer-Based Metric for Augmented Reality Quality Assessment
journal Signal Processing: Image Communication, vol. 140, art. 117437
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ARaBIQA: A Novel Blind Image Quality Assessment Model for Augmented Reality
conference IEEE International Conference on Image Processing (ICIP), pp. 379–384
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Lightweight Image Quality Prediction Guided by Perceptual Ranking Feedback
conference IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Towards Light-Weight Transformer-Based Quality Assessment Metric for Augmented Reality
conference IEEE 26th International Workshop on Multimedia Signal Processing (MMSP)
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Shifting Focus: From Global Semantics to Local Prominent Features in Swin-Transformer for Knee Osteoarthritis Severity Assessment
conference 32nd European Signal Processing Conference (EUSIPCO), pp. 1686–1690
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Do Digital Images Tell the Truth?
chapter Digital Image Security: Techniques and Applications, CRC Press, pp. 247–265
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Automatic Diagnosis of Knee Osteoarthritis Severity Using Swin Transformer
conference 20th International Conference on Content-Based Multimedia Indexing (CBMI)
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Diagnostic automatique de la sévérité de la gonarthrose à l'aide de transformeur Swin
conference Colloque GRETSI sur le traitement du signal et des images (in French)
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Deep-Based Quality Assessment of Medical Images Through Domain Adaptation
conference IEEE International Conference on Image Processing (ICIP), pp. 3692–3696
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Évaluation de la qualité des images médicales basée sur un apprentissage par adaptation au domaine
conference Colloque GRETSI sur le traitement du signal et des images (in French)
Profiles
- Google Scholar — citations and metrics
- ORCID — 0000-0002-0958-9478
- ResearchGate — Aymen Sekhri
- GitHub — AymenSe
- LinkedIn — aymensekhri1