large vision model (LVM)
Large Vision Models (LVMs) are a class of artificial intelligence models that are designed to understand and interpret visual information. They are analogous to Large Language Models (LLMs) but are focused on the visual domain rather than text. LVMs can process and generate visual content, and they are expected to play a significant role in the future of AI by integrating with LLMs to create comprehensive systems capable of understanding both text and images[1].
LVMs are trained on large datasets, which may include a wide variety of images covering numerous objects and modalities such as CT, MRI, X-ray, and ultrasound in the case of medical imaging. For example, LVM-Med is a large-scale self-supervised vision model specifically designed for medical imaging, which has been shown to outperform other models in tasks like brain tumor classification or diabetic retinopathy grading[2][3].
The development of LVMs involves significant computational resources for training and deployment, and there are important considerations regarding accessibility and privacy, especially when used in applications like surveillance[1]. Despite these challenges, LVMs have the potential to transform fields such as healthcare by enabling the development of models over distributed datasets without compromising patient privacy[8].
In terms of applications, LVMs can be used in various sectors, including the food industry for tasks like object detection, image segmentation, and visual prompting. Companies like Landing AI have been working on domain-specific LVMs, which are foundation models trained on proprietary datasets to perform high-performance downstream computer vision tasks[4][7].
In conclusion, LVMs represent a significant advancement in the field of AI, with the potential to revolutionize how visual information is processed and understood. They are set to become increasingly influential as the technology matures, offering scalable, adaptable, and privacy-preserving solutions for leveraging distributed data sources[1][2][3][4][7][8].
Citations:
[1] https://innodata.com/what-are-large-vision-models-lvm/
[2] https://arxiv.org/abs/2306.11925
[3] https://openreview.net/pdf?id=xE7oH5iVGK
[5] https://proceedings.mlr.press/v97/lawrence19a.html
[6] https://arxiv.org/abs/2208.10847
[10] https://www.youtube.com/watch?v=29USE4U5IXo
[11] https://privacy-preserving-machine-learning.github.io/LL_LVM_NIPS_2015.pdf
[12] https://landing.ai
[13] https://www.wallstreetmojo.com/latent-variable-model/
[15] https://yutongbai.com/lvm.html
[17] https://www.linkedin.com/pulse/domain-specific-large-vision-models-revolutionizing-way-we-wewge