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GRUSpam: robust e-mail spam detection using gated recurrent unit (GRU) algorithm
Email is one of the most popular communication tools for delivering messages online. However, tremendously delivered email has harmed users through...
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Motion feature estimation using bi-directional GRU for skeleton-based dynamic hand gesture recognition
Dynamic hand gesture recognition continues to be an interesting field in computer vision applications. Occlusion and background clutter make dynamic...
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A Light-Weighted Model of GRU + CNN Hybrid for Network Intrusion Detection
Typical network traffic is characterized by high-dimensional, polymorphic and massive amounts of data, which is a consistent challenge for...
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An efficient two-state GRU based on feature attention mechanism for sentiment analysis
Sentiment analysis is one of the most challenging tasks in natural language processing (NLP). The extensively used application of sentiment analysis...
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An energy aware resource allocation based on combination of CNN and GRU for virtual machine selection
The use of cloud computing service models is rapidly increasing, but inefficient resource usage in cloud data centers can lead to great energy...
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A hybrid approach of Poisson distribution LDA with deep Siamese Bi-LSTM and GRU model for semantic similarity prediction for text data
Prediction of semantic similarity between text data is an open and challenging research issue in the NLP-Natural Language-processing field....
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A novel approach for software defect prediction using CNN and GRU based on SMOTE Tomek method
Software defect prediction (SDP) plays a vital role in enhancing the quality of software projects and reducing maintenance-based risks through the...
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A deep learning approach to dysarthric utterance classification with BiLSTM-GRU, speech cue filtering, and log mel spectrograms
Assessing the intelligibility of dysarthric speech, characterized by intricate speaking rhythms presents formidable challenges. Current techniques...
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A LSTM and GRU-Based Hybrid Model in the Cryptocurrency Price Prediction
Cryptocurrency is a new type of digital currency that utilizes blockchain technology and cryptography to achieve transparency, decentralization, and...
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Refinement of ensemble strategy for acute lymphoblastic leukemia microscopic images using hybrid CNN-GRU-BiLSTM and MSVM classifier
Acute lymphocytic leukemia (ALL) is a common serious cancer in white blood cells (WBC) that advances quickly and produces abnormal cells in the bone...
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Visual feature-based improved EfficientNet-GRU for Fritillariae Cirrhosae Bulbus identification
Fritillariae Cirrhosae Bulbus (FCB) as a well-known traditional Chinese Medicine (TCM), which is widely used for its ability of relieving cough and...
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MhSa-GRU: combining user’s dynamic preferences and items’ correlation to augment sequence recommendation
Product recommendation systems have become an effective tool to help users make choices under information overload. For sequence recommendation, the...
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A distributed EMDN-GRU model on Spark for passenger waiting time forecasting
It is hard to forecast waiting time from mobile trajectory big data on the traditional centralized mining platform, and especially the taxi driving...
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An automatic algorithm for software vulnerability classification based on CNN and GRU
In order to improve the management efficiency of software vulnerability classification, reduce the risk of system being attacked and destroyed, and...
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A GRU and chaos-based novel image encryption approach for transport images
An Intelligent Transport System (ITS) uses smart devices to capture the traffic data in the form of images. However, the adversary can steal and...
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Comparative Analysis of the Effect of KPCA in PSO-GRU Combination Model
Considering the issues of strong coupling, complex fault mode and nonlinear relationship between variables in marine condensate feed water system,...
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Multivariate workload and resource prediction in cloud computing using CNN and GRU by attention mechanism
The resources required to service cloud computing applications are dynamic and fluctuate over time in response to variations in the volume of...
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Optimized recurrent neural network based brain emotion recognition technique
In this paper, a brain emotion recognition model is developed for EEG signal-based emotion recognition using the dataset from Kaggle implementing a...
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Routing hypergraph convolutional recurrent network for network traffic prediction
Effectively predicting network traffic is a fundamental but intractable task in IP network management and operations. Many methods that can capture...
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EEG pattern identification for motor imagery based on 1DCNN-GRU
Due to unique secrecy, vividness, and unpredictability, electroencephalogram signals are regarded an efficient method of identification for security...
