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 ...

Encoder-Decoder Seq2Seq (Sequence-to-Sequence) is a type of neural network architecture used for machine translation, speech recognition, and other natural language processing tasks. The ...

Encoder and Decoder Architecture. In 2015, Sequence to Sequence Learning with Neural Network became a very popular architecture and with that the encoder-decoder architecture also became part of wide ...

Encoder-Decoder Architectures. Encoder-decoder architectures are a broad category of models used primarily for tasks that involve transforming input data into output data of a different form or ...

Abstract: In this paper, we propose a deep learning based vehicle trajectory prediction technique which can generate the future trajectory sequence of surrounding vehicles in real time. We employ the ...

Encoder-Decoder Seq2Seq (Sequence-to-Sequence) is a type of neural network architecture used for machine translation, speech recognition, and other natural language processing tasks. The ...

In this paper, we propose a deep learning based vehicle trajectory prediction technique which can generate the future trajectory sequence of surrounding vehicles in real time. We employ the ...