In a survey study of U.S. teens, more than half (55.3%) reported that they had created at least one image using nudification ...

DoorDash has launched a multimodal machine learning system that aligns product images, text, and user queries in a shared ...

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...

ABSTRACT: Corrosion is one of the most challenging problems that affects the safety and durability of onshore pipelines. Corrosion-resistant steels play a pivotal role in ensuring long lasting ...

It’s everywhere, as the author learned the hard way while making as little contact as possible with machine learning and generative artificial intelligence. It’s everywhere, as the author learned the ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Abstract: This study investigates the effectiveness of combining deep learning-based feature extraction with classical machine learning classifiers for the task of litter image classification, aiming ...

Abstract: This paper presents an image-based framework for classifying fluid flow regimes into low and high-speed states by utilizing spatially localized texture features combined with machine ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

Microplastics have been found to be highly pervasive in the environment, driving concerns for health, environment, and ecology. Analytical methods that can accurately identify microplastics are ...