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Found 6 papers, 0 papers with code
CNN Autoencoder Resizer: A Power-Efficient LoS/NLoS Detector in MIMO-enabled UAV Networks
Optimizing the design, performance, and resource efficiency of wireless networks (WNs) necessitates the ability to discern Line of Sight (LoS) and Non-Line of Sight (NLoS) scenarios across diverse applications and environments.
Federated Learning: A Cutting-Edge Survey of the Latest Advancements and Applications
Robust machine learning (ML) models can be developed by leveraging large volumes of data and distributing the computational tasks across numerous devices or servers.
The Looming Threat of Fake and LLM-generated LinkedIn Profiles: Challenges and Opportunities for Detection and Prevention
We show that the suggested method can distinguish between legitimate and fake profiles with an accuracy of about 95% across all word embeddings.
Unsupervised Motor Imagery Saliency Detection Based on Self-Attention Mechanism
Detecting the salient parts of motor-imagery electroencephalogram (MI-EEG) signals can enhance the performance of the brain-computer interface (BCI) system and reduce the computational burden required for processing lengthy MI-EEG signals.
A Subject-Independent Brain-Computer Interface Framework Based on Supervised Autoencoder
Developing a subject-independent MI-BCI system to reduce the calibration phase is still challenging due to the subject-dependent characteristics of the MI signals.
A self-paced BCI system with low latency for motor imagery onset detection based on time series prediction paradigm
In a self-paced motor-imagery brain-computer interface (MI-BCI), the onsets of the MI commands presented in a continuous electroencephalogram (EEG) signal are unknown.
