Browsing Faculty Contributions by Title
Now showing items 4121-4140 of 16840
-
Deep learning in classifying sleep stages
( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)This paper presents a deep feed-forward neural network classifier to automatically classify the stages of sleep using raw data taken from a single electropalatogram channel (Fpz-Cz). No features are extracted at all from ... -
Deep learning models for sentiment analysis in arabic
( Association for Computational Linguistics (ACL) , 2015 , Conference Paper)In this paper, deep learning framework is proposed for text sentiment classification in Arabic. Four different architectures are explored. Three are based on Deep Belief Networks and Deep Auto Encoders, where the input ... -
Deep Learning Technique for Congenital Heart Disease Detection Using Stacking-Based CNN-LSTM Models from Fetal Echocardiogram: A Pilot Study
( IEEE , 2023 , Article)Congenital heart defects (CHDs) are a leading cause of death in infants under 1 year of age. Prenatal intervention can reduce the risk of postnatal serious CHD patients, but current diagnosis is based on qualitative criteria, ... -
Deep learning techniques for liver and liver tumor segmentation: A review
( Elsevier , 2022 , Article)Liver and liver tumor segmentation from 3D volumetric images has been an active research area in the medical image processing domain for the last few decades. The existence of other organs such as the heart, spleen, stomach, ... -
A deep learning-based approach for fault diagnosis of current-carrying ring in catenary system
( Springer Science and Business Media Deutschland GmbH , 2021 , Article)In the Industrial Internet of Things, the deep learning-based methods are used to help solve various problems. The current-carrying ring as one of important components on the catenary system which is always small in the ... -
Deep Learning-Based Conjunctival Melanoma Detection Using Ocular Surface Images
( springer link , 2023 , Article)The human eye could be affected with conjunctival melanoma, which indicates a fatal malignant growth of the eye. Being a very rare disease, there exists a lack of related data in the literature. Also, very few studies ... -
Deep Learning-Based Defect Prediction for Mobile Applications
( MDPI , 2022 , Article)Smartphones have enabled the widespread use of mobile applications. However, there are unrecognized defects of mobile applications that can affect businesses due to a negative user experience. To avoid this, the defects ... -
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 Reinforcement Learning Powered IRS-Assisted Downlink NOMA
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)In this work, we examine an intelligent reflecting surface (IRS) assisted downlink non-orthogonal multiple access (NOMA) scenario intending to maximize the sum-rate of users. The optimization problem at the IRS is quite ... -
Deep Semantic Segmentation and Multi-Class Skin Lesion Classification Based on Convolutional Neural Network
( IEEE , 2020 , Article)Skin cancer is developed due to abnormal cell growth. These cells are grown rapidly and destroy the normal skin cells. However, it's curable at an initial stage to reduce the patient's mortality rate. In this article, the ... -
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 ...
