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Toplam kayıt 16, listelenen: 1-10
Smart Stethoscope
(IEEE, 2020)
In this study, a device named smart stethoscope that uses digital sensor technology for sound capture, active acoustics for noise cancellation and artificial intelligence (AI) for diagnosis of heart and lung diseases is ...
Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Datasets Using Deep Learning
(Springer, 2020)
Techniques used for spatio-temporal anomaly detection in an unsupervised settings has attracted great attention in recent years. It has extensive use in a wide variety of applications such as: medical diagnosis, sensor ...
Random CapsNet forest model for imbalanced malware type classification task
(Elsevier, 2021)
Behavior of malware varies depending the malware types, which affects the strategies of the system protection software. Many malware classification models, empowered by machine and/or deep learning, achieve superior ...
Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of COVID-19 Outbreak in Italy
(Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2020)
Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection. Most real-world time series data ...
Applications of ML/DL in the management of smart cities and societies based on new trends in information technologies: A systematic literature review
(Elsevier, 2022)
The goal of managing smart cities and societies is to maximize the efficient use of finite resources while enhancing the quality of life. To establish a sustainable urban existence, smart cities use some new technologies ...
Air quality prediction using CNN plus LSTM-based hybrid deep learning architecture
(Springer Heidelberg, 2022)
Air pollution prediction based on variables in environmental monitoring data gains further importance with increasing concerns about climate change and the sustainability of cities. Modeling of the complex relationships ...
Predatory Conversation Detection Using Transfer Learning Approach
(Springer International Publishing Ag, 2022)
Predatory conversation detection on social media can proactively prevent the netizens, including youngsters and children, from getting exploited by sexual predators. Earlier studies have majorly employed machine learning ...
The applications of machine learning techniques in medical data processing based on distributed computing and the Internet of Things
(Elsevier Ireland Ltd, 2023)
Medical data processing has grown into a prominent topic in the latest decades with the primary goal of maintaining patient data via new information technologies, including the Internet of Things (IoT) and sensor technologies, ...
A privacy-aware method for COVID-19 detection in chest CT images using lightweight deep conventional neural network and blockchain
(Pergamon-Elsevier Science Ltd, 2022)
With the global spread of the COVID-19 epidemic, a reliable method is required for identifying COVID-19 victims. The biggest issue in detecting the virus is a lack of testing kits that are both reliable and affordable. Due ...
Regression of Large-Scale Path Loss Parameters Using Deep Neural Networks
(IEEE-Inst Electrical Electronics Engineers Inc, 2022)
Path loss exponent and shadowing factor are among important wireless channel parameters. These parameters can be estimated using field measurements or ray-tracing simulations, which are costly and time-consuming. In this ...