Slator

A Primer on Decoder-Only vs Encoder-Decoder Models for AI Translation

Large language models (LLMs) have changed the game for machine translation (MT). LLMs vary in architecture, ranging from decoder-only designs to encoder-decoder frameworks. Encoder-decoder models, ...
Analytics India Magazine

Using Encoder-Decoder LSTM in Univariate Horizon Style for Time Series Modelling

The time-series data is a type of sequential data and encoder-decoder models are very good with the sequential data and the reason behind this capability is the LSTM or RNN layer in the network.
inc42

What Is Encoder-Decoder Architecture? Here’s All You Need to Know

What Is An Encoder-Decoder Architecture? 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 ...
GitHub

Machine Translation using Encoder-Decoder Architecture

A deep learning-based Machine Translation system that translates text from one language to another using an Encoder-Decoder architecture with attention mechanism. Built using TensorFlow, Keras, and ...
IEEE

Encoder-Decoder based Segmentation Model for UAV Street Scene Images

Abstract: Global contextual information needs to be modeled precisely for accurate segmentation of images taken by Unmanned Aerial Vehicles (UAVs). This paper presents a transformer-based method for ...
IEEE

ESNet: Anti-Hierarchical Encoder–Decoder Network With Surrounding Expansion and Stripping for Hyperspectral Image Classification

Abstract: Spatial information is crucial in deep spectral–spatial hyperspectral image (HSI) classification methods. Spatial features can be divided into central features and surrounding features, ...
GitHub

Encoder-Decoder course notebook from Google

This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text ...