Computer Vision - IBM Research
2023年2月15日 · Modern computer vision systems have superhuman accuracy when it comes to image recognition and analysis, but they don’t really understand what they see. At IBM Research, we’re designing AI systems with the ability to see the world like we do.
Visual Prompting - IBM Research
Visual Prompting is a paradigm shift in the field of computer vision: being able to build an accurate segmentation model in just a few seconds of work was unthinkable a few years ago. The benefit of this technology lies in its application in technical domains, where the available data is usually limited, and new models are needed on a daily basis.
A new way to generate synthetic data for pretraining computer …
2022年6月23日 · In a pair of papers at this year’s Computer Vision and Pattern Recognition Conference , IBM researchers show that an image classifier pretrained on synthetic data and fine-tuned on real data for tasks, did as well as one trained exclusively on ImageNet’s database of real-world photos. Their classifier even proved capable of transferring its ...
Inspecto – Large Vision Model Inspection Service - IBM Research
General AI for computer vision is experiencing a surge of innovation fueled by the advent of vision transformers and Large Vision Models (LVMs). At IBM Research, we extended this technology to work for enterprise visual inspection, such as for infrastructure, automotive, manufacturing lines, quality control, and other domains where defects are ...
Challenges in post-training quantization of Vision Transformers
Vision Transformers recently showed outstanding performance in computer vision tasks. However, those models are compute and memory intensive that require accelerators with a large amount of memory like NVIDIA A100 graphic processing unit for training and even for inference.
Brown Ebouky - IBM Research
Using AI to build computer vision models within minutes, through quick intuitive prompts, and with just a few images Inspecto – Large Vision Model Inspection Service Increasing speed and quality of enterprise visual inspection, leveraging AI and domain-specific Large Vision Models
Roy Assaf - IBM Research
His research is focused on deep learning for Computer Vision, particularly in the context of Foundation Models. He leads the Foundation Models for Computer Vision project which aims to i) Develop Self-Supervised learning methods for training Foundation Models and ii) Develop tuning methods (Fine tuning, prompt tuning and in-context learning ...
Fine-tuning geospatial models made easier - IBM Research
2024年5月21日 · The success of foundation models for language and code has paved the way for flexible, generalizable AI for just about any domain. This includes Earth’s climate, where advanced AI vision transformers can now handle the intricacies of geospatial data from sources like Earth-observing satellites and long-term climate simulations.
Kevin Eykholt - IBM Research
Kevin Eykholt is a Research Staff Member at the IBM T.J. Watson Research Center. He earned his Ph.D in computer science at the University of Michigan Ann Arbor. During his time there, he designed one of the first physical adversarial attacks on computer vision classifiers and object detectors through the use of small adversarial stickers.
Artificial Intelligence - IBM Research
2024年12月20日 · At IBM Research, we’re designing powerful new foundation models and generative AI systems with trust and transparency at their core. We’re working to drastically lower the barrier to entry for AI development, and to do that, we’re committed to an open-source approach to enterprise AI.