Abstract: This paper presents a novel auto-encoder ... code algebraic properties. An edge-weighted GNN (EW-GNN) decoder is proposed, which operates on the Tanner graph with an iterative ...

Lastly, ViT’s self-attention design has a quadratic ... Figure 2. The same encoder-decoder architecture highlighting the operations used in the P-DeSeRay model. Similar to Swin-T, the ConvNeXt blocks ...

(Nanowerk News) Global precision motion control and nanopositioning industry leader PI introduces a new high dynamics linear motor stage family ... ensuring longevity in demanding 24/7 operations.

Our spatial attention formulation is efficient having linear ... to the encoder, whose outputs are then connected to the decoder via skip connections followed by convolutional blocks to produce the ...

POSITAL's measuring wheels and accessories leverage the company’s IXARC encoders to measure linear motion in conveyor systems, the manufacture of rolled or roll-to-roll products, and similar ...

What Is An Encoder-Decoder Architecture? An encoder-decoder architecture is a powerful tool used in machine learning, specifically for tasks involving sequences like text or speech. It’s like a ...

The decoder module integrates a convolutional block attention ... In the encoder part, we chose ShuffleNet v2 (Ma et al., 2018), an advanced lightweight network architecture, as the feature extractor ...

An interpretable auto-encoder (AE) architecture is proposed, ensuring scalability to block sizes currently challenging for ML-based linear block code design approaches. By optimizing a coding scheme w ...