While Encoder-Decoder-based neural networks have shown noticeable improvements in image restoration, their ability to further improve the image quality still remains constrained. Recent advancements ...

To fill this gap, we propose two attention-mechanism-based encoder–decoder models that incorporate multisource information: one is MAEDDI, which can predict DDIs, and the other is MAEDDIE, which can ...

The goal of this project is to implement a Transformer-based model for speech-to-text transcription, following an encoder-decoder architecture with multi-head attention mechanisms. The system ...

We introduce O-SegNet- the robust encoder and decoder architecture for objects segmentation from high-resolution aerial imagery data to address this challenge. The proposed O-SegNet architecture ...

We introduce Fourier mixed window attention (FWin) to the self-attention blocks in the encoder and decoder of Informer. Specifically, we replace the ProbSparse self-attention blocks in the encoder and ...

. ├── model.py # All model components: encoder, decoder, attention ├── mnist_generator.py # Custom dataset with tiling and blanks (scattered for future exploration) ├── training.py # Training loop ...