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LinkedIn2y
How do you choose the best encoder-decoder architecture for your seq2seq model?
If they are very long, you might need a more complex encoder-decoder architecture that can handle the long-term dependencies and avoid information loss ... a transformer model, which uses self ...
GitHub1y
understanding-of-LLM-Encoder-and-decoder-model-
An Encoder-Decoder model is a fundamental architecture in the field of deep ... Training Objectives: Decoders are often trained using various objectives such as cross-entropy loss for sequence ...
IEEE2y
Correlation Encoder-Decoder Model for Text Generation
Similar problems also confuse the implementation of the decoder. How to reduce the problem of information loss in the encoder-decoder model is critical for text generation. To address this issue, we ...
IEEE2y
A Robust Light-Weight Fused-Feature Encoder-Decoder Model for Monocular Facial Depth Estimation From Single Images Trained on Synthetic Data
To improve the prediction of depth maps, this paper proposed a lightweight neural facial depth estimation model based on single image frames. Following a basic encoder-decoder network design ...
Frontiers1y
A segmentation network for farmland ridge based on encoder-decoder architecture in combined with strip pooling module and ASPP
As the model is trained, the loss function values decrease ... Considering the effectiveness of atrous convolution, this study adds ASPP module in the middle of encoder and decoder. By using the ...
GitHub1y
Encoder-Decoder Model Arch. for Creating Depth Estimation
Following a standard encoder-decoder architecture ... Even for a very simple decoder, our method is able to achieve detailed high-resolution depth maps. Global-Local Path Networks (GLPN) model trained ...