Large Language Models (LLMs) are quickly transforming the domain of Artificial Intelligence (AI), driving innovations from ...

The automotive human-machine interface (HMI) market is becoming a vital component of modern vehicle technology, ...

Many books on artificial intelligence (AI) illuminate the pathologies of AI. These pathologies are created by artificial ...

Using Google Earth imagery and 2019-2022 Sentinel-2 datasets, Chinese scientists have developed a two-stage classification framework to obtain the annual global dataset of solar photovoltaic panels at ...

This results in low sample efficiency as models must generate and test ... and CUHK has proposed a reinforcement learning framework that eliminates the need for explicit step-wise annotations using ...

VML introduces a new framework of machine learning. Unlike conventional machine learning models that are typically optimized over a continuous parameter space, VML constrains the parameter space to be ...

Reinforcement Learning ... the framework demonstrated its adaptability and efficiency, surpassing the scores of previous state-of-the-art algorithms. In conclusion, EZ-V2 presents a significant leap ...

Code from the TensorFlow Model Garden provides examples of best practices ... The result is a machine learning framework that is easier to work with—for example, by using the relatively simple ...

Apple's MLX combines familiar APIs, composable function transformations, and lazy computation to create a machine learning framework inspired ... repo includes several examples of how to use ...

Abstract: In the internet of things (IoT) networks, machine learning (ML ... This encourages us to propose an evasion framework named IF-MalEvade, based on Generative Adversarial Network (GAN) and ...