Large ai models in health informatics: Applications, challenges, and the future

J Qiu, L Li, J Sun, J Peng, P Shi… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Large AI models, or foundation models, are models recently emerging with massive scales
both parameter-wise and data-wise, the magnitudes of which can reach beyond billions …

On the challenges and perspectives of foundation models for medical image analysis

S Zhang, D Metaxas - Medical image analysis, 2024 - Elsevier
This article discusses the opportunities, applications and future directions of large-scale
pretrained models, ie, foundation models, which promise to significantly improve the …

Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Z Chen, J Wu, W Wang, W Su, G Chen… - Proceedings of the …, 2024 - openaccess.thecvf.com
The exponential growth of large language models (LLMs) has opened up numerous
possibilities for multi-modal AGI systems. However the progress in vision and vision …

End-to-end autonomous driving: Challenges and frontiers

L Chen, P Wu, K Chitta, B Jaeger… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The autonomous driving community has witnessed a rapid growth in approaches that
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …

Reproducible scaling laws for contrastive language-image learning

M Cherti, R Beaumont, R Wightman… - Proceedings of the …, 2023 - openaccess.thecvf.com
Scaling up neural networks has led to remarkable performance across a wide range of
tasks. Moreover, performance often follows reliable scaling laws as a function of training set …