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Power optimization of a single-core processor using LSTM based encoder–decoder model for online DVFS
Due to the interaction and interdependency between various hardware/software units and policies of the processors with application running on it,...
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Quantum Mayfly Optimization with Encoder-Decoder Driven LSTM Networks for Malware Detection and Classification Model
Malware refers to malicious software developed to penetrate or damage a computer system without any owner’s informed consent. It uses target system...
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Development and implementation of real-time anomaly detection on tool wear based on stacked LSTM encoder-decoder model
A severe tool wear is often encountered during the process of turning/milling difficult-to-cut materials like Inconel 718. To protect the cutting...
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A Bi-GRU-based encoder–decoder framework for multivariate time series forecasting
Drought forecasting is crucial for minimizing the effects of drought, alerting people to its dangers, and assisting decision-makers in taking...
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Action-Aware Encoder-Decoder Network for Pedestrian Trajectory Prediction
Accurate pedestrian trajectory predictions are critical in self-driving systems, as they are fundamental to the response- and decision-making of ego...
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An attention encoder-decoder RNN model with teacher forcing for predicting consumer price index
The aftermath of the COVID-19 pandemic has led to a global surge in inflation rates across the world, eroding consumer purchasing power and sparking...
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Encoder–Decoder (LSTM-LSTM) Network-Based Prediction Model for Trend Forecasting in Currency Market
Trend prediction of exchange rates has been a challenging topic of research. This problem is studied using non-stationary pattern recognition...
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Enhancing Text Classification with Modular Deep Encoder-Decoder Networks for Multi-modal Data
Our study centers on a Modular Deep Encoder-Decoder network (MDED) about text classification. The basic idea behind MDED is to extend a pre-trained...
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Recurrent and convolutional neural networks in structural dynamics: a modified attention steered encoder–decoder architecture versus LSTM versus GRU versus TCN topologies to predict the response of shock wave-loaded plates
The aim of the present study is to analyse and predict the structural deformations occurring during shock tube experiments with a series of recurrent...
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Image Captioning Encoder–Decoder Models Using CNN-RNN Architectures: A Comparative Study
An image caption generator produces syntactically and semantically correct sentences to narrate the scene of a natural image. A neural image caption...
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Integrated encoder-decoder-based wide and deep convolution neural networks strategy for electricity theft arbitration
Integrating energy systems with information systems in smart grids offers a promising avenue for combating electricity theft by leveraging real-time...
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Long short-term memory based semi-supervised encoder—decoder for early prediction of failures in self-lubricating bearings
The existing knowledge regarding the interfacial forces, lubrication, and wear of bearings in real-world operation has significantly improved their...
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Comparative Analysis of LSTM, Encoder-Decoder and GRU Models for Stock Price Prediction
The stock market is a venue where shares of publicly traded enterprises can be bought and sold on a regular basis. It is a vital component of any...
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Automatic Text Simplification Using LSTM Encoder Decoder Model
The text simplification is a process of simplifying the natural language in such a way that it became easier to understand and to read the language....
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Deep encoder/decoder dual-path neural network for speech separation in noisy reverberation environments
In recent years, the speaker-independent, single-channel speech separation problem has made significant progress with the development of deep neural...
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LSTM-Based Encoder–Decoder Model for Transliteration of English, Marathi, and Hindi Query
The World Wide Web search is the most vital and elementary way to get knowledge and access the information. Over the globe, the information retrieval...
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LSTM with spatiotemporal attention for IoT-based wireless sensor collected hydrological time-series forecasting
It is necessary to accurately assess the inflow and infiltration conditions in sewer systems if sewer overflows are to be avoided. In this regard,...
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LSTM-Based Encoder–Decoder Attention Model for Text Translation and Simplification on the Constitution of India
Natural language processing techniques can be used on judicial and legislative documents like the Constitution for making it more accessible to the...
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Performance Analysis of Image Caption Generation Techniques Using CNN-Based Encoder–Decoder Architecture
Image captioning is the method of generating textual descriptions for an image using deep neural networks. Its objective is to produce accurate...
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BaNeL: an encoder-decoder based Bangla neural lemmatizer
AbstractThis study presents an efficient framework of deriving lemma from an inflected Bangla word considering its parts-of-speech as context. Bangla...
