This project is a simple implementation of an Encoder-Decoder model using LSTM to perform English to French translation on a small set of sentence pairs. Built and tested in Google Colab, the model ...

Abstract: This study introduces an innovative deep learning framework, the Weber Cross Information Sharing Deep Learning Encoder-Decoder (WCISD-ED) model, designed for emotion recognition through ...

Google has launched T5Gemma, a new collection of encoder-decoder large language models (LLMs) that promise improved quality and inference efficiency compared to their decoder-only counterparts. It is ...

This repository provides the code for the paper: Giuseppe La Tona and Maria Carmela Di Piazza, "Enhanced Day-Ahead Solar Irradiance Forecasting Using a Modified LSTM Encoder-Decoder: A Deep Learning ...

Abstract: In this letter, we propose a deep learning-based iterative residual encoder-decoder method (IRED), which provides an efficient deep learning framework for electromagnetic modeling over a ...

Hold on - AI and Deep Learning are that easy? Of course, it’s not that easy: There is a big difference between using a model and training a model. Before we can reach the point where we have such a ...

Quadrature encoders have many uses in position-sensing applications. This implementation uses a Xilinx complex programmable logic device (CPLD) to count the pulses ...

In this paper, we introduce the world’s first 8K 120-Hz video real-time encoder and decoder that complies with ARIB STD-B32 1) . We evaluated the coding efficiency and demonstrated that 8K 120-Hz ...