Results 241 to 250 of about 274,921 (303)
Behavioral Intruder Detection Based on Browsing Patterns with Automated Grouping of Requested Webpages. [PDF]
Wilczek A, Ciecierski K, Kamola M.
europepmc +1 more source
Low-Cost Sensors in 5G RF-EMF Exposure Monitoring: Validity and Challenges. [PDF]
Rathebe PC, Kholopo M.
europepmc +1 more source
Review on enhancing clinical decision support system using machine learning
Abstract Clinical decision‐making is a complex patient‐centred process. For an informed clinical decision, the input data is very thorough ranging from detailed family history, environmental history, social history, health‐risk assessments, and prior relevant medical cases.
Anum Masood +4 more
wiley +1 more source
Mission-Critical Services in 4G/5G and Beyond: Standardization, Key Challenges, and Future Perspectives. [PDF]
Rastoceanu F +5 more
europepmc +1 more source
Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help ...
Chandramohan Dhasaratha +9 more
wiley +1 more source
Precision cotton disease detection via transformer models applied to leaf imagery. [PDF]
Inamdar N +5 more
europepmc +1 more source
Graph neural network‐based attack prediction for communication‐based train control systems
Abstract The Advanced Persistent Threats (APTs) have emerged as one of the key security challenges to industrial control systems. APTs are complex multi‐step attacks, and they are naturally diverse and complex. Therefore, it is important to comprehend the behaviour of APT attackers and anticipate the upcoming attack actions.
Junyi Zhao +3 more
wiley +1 more source
Superimposed CSI Feedback Assisted by Inactive Sensing Information. [PDF]
Zhang M +6 more
europepmc +1 more source
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma +4 more
wiley +1 more source

