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IEEE5y
A Novel Deep Learning-Based Encoder-Decoder Model for Remaining Useful Life Prediction
Abstract: A novel encoder-decoder model based on deep neural networks is proposed for the prediction of remaining useful life (RUL) in this work. The proposed model consists of an encoder and a ...
marktechpost1y
Deep Learning Architectures From CNN, RNN, GAN, and Transformers To Encoder-Decoder Architectures
Attention mechanisms, especially in transformer models, have significantly enhanced the performance of encoder-decoder architectures, making them highly effective for a wide range of ...
GitHub3mon
Image Colorization Using Deep Learning
This project aims to colorize grayscale images using a deep learning model that combines a Convolutional Neural Network (CNN) for feature extraction and InceptionResNetV2 for enhanced colorization.
Frontiers1y
An image caption model based on attention mechanism and deep reinforcement learning
considering the powerful perception and decision abilities of Deep Reinforcement Learning (DRL), this paper constructs a training optimization method based on DRL to improve the overall performance of ...
GitHub3y
matlab-deep-learning/pretrained-salsanext
This pretrained model is trained using Pandaset dataset[2] which has ... SalsaNext was build upon SalsaNet that has encoder-decoder architecture with residual dilated convolution stack with gradually ...
IEEE5y
A Novel Deep Learning-Based Encoder-Decoder Model for Remaining Useful Life Prediction
Abstract: A novel encoder-decoder model based on deep neural networks is proposed for the prediction of remaining useful life (RUL) in this work. The proposed model consists of an encoder and a ...