(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 ...

This figure shows how the STAIG framework can successfully identify spatial domains by integrating image processing and contrastive learning to analyze spatial transcriptomics data effectively.

Deep learning techniques can enhance diagnosis of Meniere disease (MD) and severity grading, according to a study published ...

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

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 ...

Detecting concealed explosives and chemical threats constitutes a critical challenge in global security, yet current technologies often face significant operational limitations. While X-ray scanners ...

Ultrasound (US) imaging is a widely employed diagnostic tool used for real-time imaging of various organs and tissues using ultrasonic sound waves. The waves are sent into the body, and images are ...

A new learning paradigm developed by University College London (UCL) and Huawei Noah’s Ark Lab enables large language model (LLM) agents to dynamically adapt to their environment without fine-tuning ...

South Korean researchers have developed a guided-learning framework that accurately predicts PV power without requiring irradiance sensors during operation, using routine meteorological data instead.

WASHINGTON--(BUSINESS WIRE)--WorldQuant University (WQU) has launched the Deep Learning Fundamentals Lab, a free, 16-week online certificate program designed to equip learners with advanced technical ...