Metabolite identification from 1D 1H NMR spectra is a major challenge in NMR-based metabolomics. This study introduces NMRformer, a Transformer-based deep learning framework for accurate peak ...

To suppress noise and artifacts caused by the reduced radiation exposure in low-dose computed tomography, several deep learning (DL)-based image restoration methods have been proposed over the past ...

This is achieved via a global encoder-decoder attention sub-module from the input data directly, as well as learning different local channel-wise and spatial attention contexts tailored for individual ...

This was one of the technical advances that enabled deep learning to outperform previous methods for object recognition, 60 as outlined here. Breakthroughs in speech and object recognition. An ...

To learn disentangled representations of facial images, we present a Dual Encoder-Decoder based Generative Adversarial Network (DED-GAN). In the proposed method, both the generator and discriminator ...