Researchers have demonstrated, for the first time, that transfer learning can significantly enhance material Z-class identification in muon tomography, even in scenarios with limited or completely ...

Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...

ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...

Abstract: Quantum neural networks (QNNs) have attracted significant attention recently, primarily because of their potential to address complex problems deemed difficult for traditional computational ...

Introduction: Alzheimer’s disease (AD) is one of the most common neurodegenerative disabilities that often leads to memory loss, confusion, difficulty in language and trouble with motor coordination.

A new study led by researchers from the Yunnan Observatories of the Chinese Academy of Sciences has developed a neural network-based method for large-scale celestial object classification, according ...

Introduction: In recent years, advancements in machine learning and electronic stethoscope technology have enabled high-precision recording and analysis of lung sounds, significantly enhancing ...

Abstract: Multiclass neural learning involves finding appropriate neural network architecture, encoding schemes, learning algorithms, etc. We discuss major approaches used in neural networks for ...