One of the most difficult challenges in payment card fraud detection is extreme class imbalance. Fraudulent transactions ...

A new study presents a zero-shot learning (ZSL) framework for maize cob phenotyping, enabling the extraction of geometric ...

The deep learning field has been dominated by “large models” requiring massive computational resources and energy, leading to unsustainable environmental and economic challenges. To address this, ...

COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...

Researchers at the University of California, Los Angeles (UCLA), in collaboration with pathologists from Hadassah Hebrew ...

(a) An illustrative map for Crack-Net, including the initial features, looping solver for data generation, model training, and prediction performance. (b) The Crack-Net architecture, which utilizes ...

By combining Transformer-based sequence modeling with a novel conditional probability strategy, the approach overcomes ...

Gathering and processing this data is time consuming and expensive, limiting the models' use to areas with long-term data records and high-powered computers. To overcome these limitations, the ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

Linux has long been the backbone of modern computing, serving as the foundation for servers, cloud infrastructures, embedded systems, and supercomputers. As artificial intelligence (AI) and machine ...