AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 2 of 2 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
PRISM (Prototype-Rectified Iterative Self-supervised Manifold Denoising), a training-free, source-free TTA framework grounded in the Affine Noise Hypothesis, is addressed, making it substantially faster than gradient-based TTA while requiring no additional training.
An overview of the most prominent types of AI models employed in smart traffic control and road safety, such as supervised and unsupervised machine learning, deep learning, computer vision, and reinforcement learning, and their applications for traffic flow prediction, adaptive traffic signal control, vehicle and pedestrian detection, accident prediction, driver behaviour monitoring, and prioritisation of emergency vehicles are discussed.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.