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GitHub2mon
Image-Captioning-with-Encoder-Decoder-Architecture-Using-Deep-Learning
The model leverages the Inception v3 pre-trained model for feature extraction from images and an LSTM-based decoder to generate captions. The architecture follows an encoder-decoder structure where ...
IEEE2d
DRL-ED-TSPP: A Deep Reinforcement Learning Model With Encoder-Decoder for Solving the Traveling Salesman Problem With Profits
DRL-ED-TSPP: A Deep Reinforcement Learning Model With Encoder-Decoder for Solving the Traveling Salesman Problem With Profits Abstract: The rapid growth of smart cultural tourism necessitates ...
IEEE5y
A Novel Deep Learning-Based Encoder-Decoder Model for Remaining Useful ...
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 decoder. In the ...
University of Waterloo2y
Quantile-Based Encoder-Decoder Deep Learning Models for Multi-Step Ahead Hydrological Forecasting | Dr. John M. Quilty - University of Waterloo
Quantile-Based Encoder-Decoder Deep Learning Models for Multi-Step Ahead Hydrological Forecasting [Conference presentation]. American Geophysical Union (AGU) Fall Meeting 2022, Online. Recent ...
GitHub8mon
GitHub - saaimzr/Encoder-Decoder-Transformer-Model-for-Vector-to-Vector-Computation: A Transformer model built from scratch to perform basic arithmetic operations, implementing ...
A Transformer model built from scratch to perform basic arithmetic operations, implementing multi-head attention, feed-forward layers, and layer normalization from the Attention is All You Need paper.
marktechpost1y
Deep Learning Architectures From CNN, RNN, GAN, and Transformers To Encoder-Decoder Architectures - MarkTechPost
This article explores some of the most influential deep learning architectures: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), ...