IEEE IJCNN 2025 Special Session on Data-efficient Vision Transformers
Join Us at IJCNN 2025 for Our Special Session on Data-efficient Vision Transformers. For more details visit
We are thrilled to announce our special session, “Data-efficient Vision Transformers: Challenges & Applications”, which will take place during the IEEE International Joint Conference on Neural Networks (IEEE IJCNN 2025 2025) in Rome, Italy, from 30 June to 5 July 2025.
About the Session
Vision Transformers (ViTs) are reshaping computer vision with state-of-the-art performance across various domains. However, their dependency on large datasets often limits their potential in real-world, data-scarce scenarios. This special session focuses on innovative methods to enhance data efficiency in ViTs, including self-supervised learning, transfer learning, and generative augmentation strategies.
Why Attend?
Explore cutting-edge techniques for optimising ViTs for low-data regimes. Engage with experts from academia, industry, and research institutions. Discover real-world applications in healthcare, autonomous systems, and more. Participate in discussions on future directions and emerging challenges.
Key Topics
- Data-efficient training methods
- Self-supervised and few-shot learning
- Model compression and optimisation
- Applications in resource-constrained environments
- Generative models for synthetic data augmentation
Organisers
- Dr. Haider Raza, University of Essex, UK
- Dr. Muhammad Haris Khan, MBZUAI, UAE
- Professor John Q Gan, University of Essex, UK
We look forward to welcoming researchers, practitioners, and industry professionals passionate about advancing Vision Transformers in practical, impactful ways. —Haider Raza
Stay tuned for submission deadlines and more details! For inquiries, feel free to reach out to us: h.raza@essex.ac.uk