Hybrid LSTM and Encoder–Decoder Architecture for Detection of Image Forgeries Abstract: With advanced image journaling tools, one can easily alter the semantic meaning of an image by exploiting ...

The Long Short-Term Memory (LSTM) neural network is well-suited to model this type of problem because it can learn long-term dependencies in the data. To make sequence-to-sequence predictions using a ...

This repository contains the implementation of a machine translation model using Encoder-Decoder architecture with Long Short-Term Memory (LSTM) cells. The model is designed to translate text from one ...

Now, let’s have a look at the architecture of the encoder-decoder model. Image source. The above image is a representation of the architecture of an encoder-decoder model. Where x is input for the ...

LSTM autoencoder is an encoder that makes use of LSTM encoder-decoder architecture to compress data using an encoder and decode it to retain original structure using a decoder. About the dataset. The ...

Kao, I., Zhou, Y., Chang, L., & Chang, F. (2020). Exploring a Long Short-Term Memory Based Encoder-Decoder Framework for Multi-Step-Ahead Flood Forecasting. Journal of ... This good performance of ...

Hybrid LSTM and Encoder–Decoder Architecture for Detection of Image Forgeries Abstract: With advanced image journaling tools, one can easily alter the semantic meaning of an image by exploiting ...