An Encoder-decoder architecture in machine learning efficiently translates one sequence data form to another.

The transformer’s encoder doesn’t just send a final step of encoding to the decoder; it transmits all hidden states and encodings.

Transformer architecture (TA) models such as BERT (bidirectional encoder representations from transformers) and GPT (generative pretrained transformer) have revolutionized natural language processing ...

Over the past decade, advancements in machine learning (ML) and deep learning (DL) have revolutionized segmentation accuracy.