A VAE-based data self- augmentation strategy could relieve the contradiction between the accuracy and the insufficient training data in ML-based semiconductor device modeling.

To tackle this problem, we propose a litho-aware data augmentation (LADA) framework to resolve the dilemma of limited data and improve the machine learning model performance. First, we pretrain the ...

As the world grapples with climate change and dwindling fossil fuel reserves, biodiesel emerges as a promising renewable ...

A research team has developed PlantCaFo, an advanced few-shot plant disease recognition model powered by foundation models, ...

NOD, a spatiotemporal deep learning framework that leverages 3D point cloud data to identify new plant organs with ...

The integration of deep learning in neuroimaging enhances diagnostic capabilities, offering new insights into neurological disorders and treatment responses.