Leveraging the transformer architecture, the SET uses a shared encoder with positional encoding and multi-head self-attention mechanisms to capture complex temporal patterns in sensor data.

The rotational position encoder is here adopted and optimized on a 1-D Convolutional Transformer Hybrid Neural Network model for fault diagnostics on power converters. The effectiveness of the ...

Transformer-based models, such as TransUNet and UNETR, combine self-attention mechanisms with convolutional encoders to capture global context effectively. Hybrid architectures like Swin-UNETR and ...

Complex model architectures, demanding runtime computations, and transformer-specific operations introduce unique challenges.

Machines are rapidly gaining the ability to perceive, interpret and interact with the visual world in ways that were once ...

Michael Bay is planning a return to the Transformers franchise, but his movie isn't the only one being considered as a G.I. Joe crossover and Transformers One helmer Josh Cooley are also in the mix ...

Con Edison crews are working to restore power for some residents on Eastchester Road in Morris Park, the Bronx, after a transformer blew.

This repository contains the implementation of our paper: "DBConformer: Dual-Branch Convolutional Transformer for EEG Decoding", serving as a benchmark codebase for EEG decoding models. We implemented ...