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.
Machine Unlearning in Computer Vision: Foundations and …
Therefore, it is crucial to meticulously review, thoroughly explore, and comprehensively survey MU for computer vision (CV) through this tutorial. Within this tutorial, we will delve into the algorithmic foundations of MU methods, including techniques such as localization-informed unlearning, unlearning-focused finetuning, and vision model ...
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 ...
A Model for Estimating the Economic Costs of Computer Vision …
In this paper, we connect technical insights from deep learning scaling laws and transfer learning with the economics of IT to propose a framework for estimating the cost of deep learning computer vision systems to achieve a desired level of accuracy.
Computer Science - IBM Research
2024年6月10日 · IBM has been at the forefront of computer science research since the field’s inception. Our research today focuses on achieving breakthroughs in automation, information processing, and computation. Our goal is to complement and extend human performance — and advance society as a whole.
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.
Automated computer vision assessment of hypomimia in …
Objective: We aimed to determine whether modern computer vision techniques can be applied to detect masked facies and quantify drug states in PD. Methods: We trained a convolutional neural network on images extracted from videos of 107 self-identified people with PD, along with 1595 videos of controls, in order to detect PD hypomimia cues.
Artificial Intelligence - IBM Research
Today's AI is narrow. Applying trained models to new challenges requires an immense amount of new data training, and time. We need AI that combines different forms of knowledge, unpacks causal relationships, and learns new things on its own. In short, AI must have fluid intelligence— and that's exactly what our AI research teams are building.
50 Years of object recognition: Directions forward for Computer …
In this paper we discuss the evolution of computer-based object recognition systems over the last fifty years, and overview the successes and failures of proposed solutions to the problem.
Blog - IBM Research
The IBM Research blog is the home for stories told by the researchers, scientists, and engineers inventing What’s Next in science and technology.