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FEDDBN-IDS: federated deep belief network-based wireless network intrusion detection system
Over the last 20 years, Wi-Fi technology has advanced to the point where most modern devices are small and rely on Wi-Fi to access the internet....
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Speech Emotion Recognition Using Generative Adversarial Network and Deep Convolutional Neural Network
Speech emotion recognition (SER) has recently increased because of vast innovations in human–computer interaction and affective computing. In recent...
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Fault Detection of Flexible DC Distribution Network Based on GAF and Improved Deep Residual Network
To solve the problems of low accuracy and susceptibility to transition resistance in the existing fault detection methods of flexible DC distribution...
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Compressed Video Sensing Based on Deep Generative Adversarial Network
This paper considers the deep-learning-aided compressed video sensing problem. To this end, a deep generative adversarial network has been proposed...
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Deep Neural Network for Solving Stochastic Biological Systems
The purpose of this paper is to introduce a new method based on the deep neural network method (DNN) for finding numerical solution of a novel class...
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Spiking SiamFC++: deep spiking neural network for object tracking
Spiking neural network (SNN) is a biologically-plausible model and exhibits advantages of high computational capability and low power consumption....
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Quantum deep learning-based anomaly detection for enhanced network security
Identifying and mitigating aberrant activities within the network traffic is important to prevent adverse consequences caused by cyber security...
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A novel interpretable multilevel wavelet decomposition deep network for actual heartbeat classification
Arrhythmias may lead to sudden cardiac death if not detected and treated in time. A supraventricular premature beat (SPB) and premature ventricular...
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D2PG: deep deterministic policy gradient based for maximizing network throughput in clustered EH-WSN
Wireless sensor networks are considered one of the effective technologies in various applications, responsible for monitoring and sensing. In these...
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Managing 5G IOT Network Operations and Safety Using Deep Learning and Attention Methods
The abstract introduces an innovative method for overseeing 5G-connected Internet of Things (IoT) networks by combining deep learning and attention...
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Improving Time Series Prediction with Deep Belief Network
In this paper, the time series data prediction is done using Deep Belief Network (DBN). The time series data chosen are stock price data, exchange...
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Chart-to-text generation using a hybrid deep network
Text generation from charts is a task that involves automatically generating natural language text descriptions of data presented in chart form. This...
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Weak signal extraction enabled by deep neural network denoising of diffraction data
The removal or cancellation of noise has wide-spread applications in imaging and acoustics. In applications in everyday life, such as image...
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New deep recurrent hybrid artificial neural network for forecasting seasonal time series
The simple recurrent artificial neural network is a deep artificial neural network frequently used in the literature for solving forecasting...
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A deep reinforcement learning-based D2D spectrum allocation underlaying a cellular network
We develop a deep reinforcement learning-based (DRL) spectrum access scheme for device-to-device communications in an underlay cellular network....
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Deep dynamic adaptation network: a deep transfer learning framework for rolling bearing fault diagnosis under variable working conditions
Many cross-domain bearings fault diagnosis approaches have been developed by researchers. However, how to reduce the shift of training and test data...
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Deep Fundamental Diagram Network for Fast Pedestrian Dynamics Estimation
How to effectively guide occupants to use different evacuation routes under fire situations is the key to improving fire safety and ensuring...
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Deep convolutional neural network-based Henry gas solubility optimization for disease prediction in data from wireless sensor network
Wireless sensor networks (WSNs) are the most promising solutions in modern technology for increased reliability, remote monitoring, tracking of...
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Multi-Agent Path Planning Method Based on Improved Deep Q-Network in Dynamic Environments
The multi-agent path planning problem presents significant challenges in dynamic environments, primarily due to the ever-changing positions of...
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A network intrusion detection framework on sparse deep denoising auto-encoder for dimensionality reduction
In today's internet-driven world, a multitude of attacks occurs daily, propelled by a vast user base. The effective detection of these numerous...
