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 two-part machine that translates one form ...

They consist of two main components: an encoder and a decoder. The encoder takes in the input sequence and encodes it into a fixed-length representation, often referred to as the context vector.

image: Examples of post-impact image sequences generated by the trained encoder–decoder and the actual binarized post-impact image sequences. view more Credit: Jingzu Yee, Daichi Igarashi, Shun ...

Eight DNA sequence inputs, specifically, D0 to D7, were thus compressed by the encoder into three electronic outputs, X, Y and Z at the redox potentials of AQ, MB and FC, respectively.