Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving ...
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.
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
A research team from the Aerospace Information Research Institute of the Chinese Academy of Sciences (AIRCAS) has developed a ...
Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Medical researchers at Mass General Brigham say the self-supervised foundational model can identify inherent features from ...
Deep learning is increasingly being used to emulate cloud and convection processes in climate models, offering a faster ...
But this breakthrough doesn't stand alone; recent developments in plastic science and recycling include pyrolysis research to ...
Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...
A research team led by Professor Wang Hongzhi from the Hefei Institute of Physical Science of the Chinese Academy of Sciences has developed a multi-stage, dual-domain, progressive network with ...
Evolving toxicity assessments for engineered nanoparticles underline the importance of predictive models and life-cycle risk ...
Dengue and chikungunya, the two mosquito-borne diseases that frequently circulate at the same time, share the same Aedes ...
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