AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...
A method to interpret artificial intelligence (AI) models used in materials discovery by analyzing their learned features has been developed by researchers from Japan. The method extracts key features ...
Google DeepMind released DiffusionGemma on June 10, 2026, an experimental open-weights model that writes text using discrete ...
Rather than generating text word by word, Google's experimental open-source model drafts entire passages simultaneously using ...
“Semiconductor lithography inspection requires reliable detection of small pattern defects such as bridge, burr, pinch, and contamination. In this study, we propose a two-stage vision-language ...
Subcortical ischemic vascular disease (SIVD), driven by cerebral small vessel disease, is commonly characterized by white matter hyperintensities and multiple lacunar infarcts, and a substantial ...
Semi-supervised learning (SSL) has emerged as a promising paradigm for medical image classification, addressing the critical challenge of limited labeled data in healthcare where expert annotation is ...
FRAM [CVPR'26] is a diffusion-based facial makeup transfer model with regional controllability. It can perform global makeup transfer and region-specific makeup transfer. A data synthesis pipeline ...
Abstract: Deep learning has shown great potential in assisting medical experts in diagnosing cerebral infarction through electroencephalogram (EEG) analysis. Classifying EEG abnormality levels is a ...
Abstract: Data augmentation effectively addresses the imbalanced-small sample data (ISSD) problem in hyperspectral image classification (HSIC). Although most methodologies extend features in the ...
Over nine days, Elon Musk’s Grok chatbot generated and posted 4.4 million images, of which at least 41 percent were sexualized images of women. By Kate Conger Dylan Freedman and Stuart A. Thompson ...
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