Artificial intelligence is accelerating material discovery and design by automating analysis, guiding experiments, and enabling predictive modeling across spectroscopy, microscopy, and synthesis.

A research team has developed a deep learning–driven computed tomography (CT) imaging pipeline that enables precise, ...

Using an extremely efficient SISO-decoder algorithm, which Efficient Channel Coding Inc (www.eccincorp.com) developed, Advanced Hardware Architectures Inc (AHA) introduced the first commercially ...

The network adopts an encoder–decoder architecture with skip connections, featuring an attention ConvNeXt block that enhances local feature extraction, a large kernel attention module that captures ...

Second, a graph autoencoder with a wavelet convolutional encoder layer and a sub-pixel convolutional decoder layer is constructed to extract domain-invariant causal features from key fault related ...

To address these limitations, this study proposes a lightweight improved DSC-DeepLabv3+ model that optimizes the encoder–decoder architecture and enhances both computational efficiency and ...

A convolutional encoder embedded the input video clip into the hidden states. It was followed by the latent ODE, ODESolver and convolutional decoders to generated the target prediction. X t n: input ...

In a major leap for artificial intelligence (AI) and photonics, researchers at the University of California, Los Angeles ...

This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors found that models based on ...