Browsing Computer Science & Engineering by Title
Now showing items 695-714 of 2288
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Deep learning-based middle cerebral artery blood flow abnormality detection using flow velocity waveform derived from transcranial Doppler ultrasound
( Elsevier , 2023 , Article)Since the brain is unlike any other organ in that it cannot store energy and has a high metabolic demand, constant blood flow is essential for healthy brain function. The maximum flow velocity waveform that is produced by ... -
Deep learning-based multi-task prediction system for plant disease and species detection
( Elsevier , 2022 , Article)The manual prediction of plant species and plant diseases is expensive, time-consuming, and requires expertise that is not always available. Automated approaches, including machine learning and deep learning, are increasingly ... -
Deep neural network-aided Gaussian message passing detection for ultra-reliable low-latency communications
( Elsevier B.V. , 2019 , Article)Ultra-reliable low-latency communications (URLLC) is a key technology in 5G supporting real-time multimedia services, which requires a low-cost signal recovery technology in the physical layer. A kind of well-known ... -
Deep Reinforcement Learning Algorithm for Smart Data Compression under NOMA-Uplink Protocol
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)One of the highly promising radio access strategies for enhancing performance in the next generation cellular communications is non-orthogonal multiple access (NOMA). NOMA offers a number of advantages including better ... -
Deep Reinforcement Learning for Network Selection over Heterogeneous Health Systems
( IEEE Computer Society , 2022 , Article)Smart health systems improve our quality oflife by integrating diverse information and technologies into health and medical practices. Such technologies can significantly improve the existing health services. However, ... -
Deep Reinforcement Learning for Network Selection over Heterogeneous Health Systems
( IEEE Computer Society , 2022 , Article)Smart health systems improve our quality oflife by integrating diverse information and technologies into health and medical practices. Such technologies can significantly improve the existing health services. However, ... -
Deep Reinforcement Learning for Real-Time Trajectory Planning in UAV Networks
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Proceedings)In Unmanned Aerial Vehicle (UAV)-enabled wireless powered sensor networks, a UAV can be employed to charge the ground sensors remotely via Wireless Power Transfer (WPT) and collect the sensory data. This paper focuses on ... -
Deep visual social distancing monitoring to combat COVID-19: A comprehensive survey
( Elsevier Ltd , 2022 , Article Review)Since the start of the COVID-19 pandemic, social distancing (SD) has played an essential role in controlling and slowing down the spread of the virus in smart cities. To ensure the respect of SD in public areas, visual SD ... -
Deep-Gap: A deep learning framework for forecasting crowdsourcing supply-demand gap based on imaging time series and residual learning
( IEEE Computer Society , 2019 , Conference Paper)Mobile crowdsourcing has become easier thanks to the widespread of smartphones capable of seamlessly collecting and pushing the desired data to cloud services. However, the success of mobile crowdsourcing relies on balancing ... -
DeepAutoD: Research on Distributed Machine Learning Oriented Scalable Mobile Communication Security Unpacking System
( IEEE Computer Society , 2022 , Article)The rapid growth of Android smart phones and abundant applications (Apps), a new security solution for distributed computing and mobile communications, has prompted many enhanced vendors to use different methods to effectively ... -
DeepWTPCA-L1: A New Deep Face Recognition Model Based on WTPCA-L1 Norm Features
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)In this paper, we propose a robust face recognition model called DeepWTPCA-L1 using WTPCA-L1 features and a CNN-LSTM architecture. First, WTPCA-L1 algorithm, composed of Three-level decomposition of discrete wavelet transform ... -
Defect deconvolution using 3rd order statistics for Ultrasonic Nondestructive Testing
( IEEE , 2007 , Conference Paper)Ultrasonic nondestructive testing (NDT) is primarily based upon the detection and classification of a defect in the field of industrial materials. This information is useful in making administrative decisions in terms of ... -
Defect Deconvolution using 4th Order Statistics for Ultrasonic Nondestructive Testing
( IEEE , 2007 , Conference Paper)Classification of defects using ultrasonic nondestructive testing (NDT) is primarily done in the field of industrial materials to provide useful information in order to assist in making administrative decisions in terms ... -
Delay minimization through joint routing and resource allocation in cognitive radio-based mesh networks
( IEEE , 2012 , Conference Paper)We consider wireless mesh networks in which the nodes are utilizing cognitive radios and try to opportunistically gain access to spectrum resources. In such networks, the timely delivery of the traffic is a challenging ... -
Delay-Aware Flow Scheduling in Low Latency Enterprise Datacenter Networks: Modeling and Performance Analysis
( Institute of Electrical and Electronics Engineers Inc. , 2017 , Article)Real-time interactive application workloads (e.g., Web search, social networking, and so on) appear in the form of a large number of mini requests and responses flowing over the datacenters' networks. They end up being ... -
Delay-Aware Scheduling and Resource Optimization with Network Function Virtualization
( Institute of Electrical and Electronics Engineers Inc. , 2016 , Conference Paper)To accelerate the implementation of network functions/middle boxes and reduce the deployment cost, recently, the concept of network function virtualization (NFV) has emerged and become a topic of much interest attracting ... -
Demand Response in HEMSs Using DRL and the Impact of Its Various Configurations and Environmental Changes
( MDPI , 2022 , Article)With smart grid advances, enormous amounts of data are made available, enabling the training of machine learning algorithms such as deep reinforcement learning (DRL). Recent research has utilized DRL to obtain optimal ... -
A Demand-Driven Incremental Deployment Strategy for Edge Computing in IoT Network
( IEEE Computer Society , 2022 , Article)Edge Computing brings great opportunities to enable the Internet of Things (IoT) vision. But the physical edge server deployment problem still poses a major challenge, which dramatically affects the service ability and ... -
Denoising different types of acoustic partial discharge signals using power spectral subtraction
( Institution of Engineering and Technology , 2018 , Article)Measuring acoustic emission (AE) of partial discharge (PD) phenomena can be adopted to estimate the condition of power transformers. However, the environmental noise encountered with AE of PD measurements negatively affects ... -
Denoising of acoustic partial discharge signals corrupted with random noise
( Institute of Electrical and Electronics Engineers Inc. , 2016 , Article)Power transformers are one of the most important and expensive electrical equipment that require online condition monitoring. Partial discharge (PD) measurement is considered the most effective and non-destructive approach ...