Search Results
Source-free Subject Adaptation for EEG-based Visual Recognition
In this paper, we introduce a novel and practical problem setup, namely source-free subject adaptation, where the source subject data are unavailable and only the pre-trained model parameters are provided for subject adaptation.
Subject Adaptive EEG-based Visual Recognition
It limits recognition systems to work only for the subjects involved in model training, which is undesirable for real-world scenarios where new subjects are frequently added.
A magnetoencephalography dataset for motor and cognitive imagery-based brain-computer interface
Recent advancements in magnetoencephalography (MEG)-based brain-computer interfaces (BCIs) have shown great potential.
Too many cooks: Bayesian inference for coordinating multi-agent collaboration
Underlying the human ability to collaborate is theory-of-mind, the ability to infer the hidden mental states that drive others to act.
Cognitively-inspired Agent-based Service Composition for Mobile & Pervasive Computing
Automatic service composition in mobile and pervasive computing faces many challenges due to the complex and highly dynamic nature of the environment.
Dynamic Service Composition Orchestrated by Cognitive Agents in Mobile & Pervasive Computing
Automatic service composition in mobile and pervasive computing faces many challenges due to the complex nature of the environment.
Benchmarking Cognitive Abilities of the Brain with Computer Games
While the user can control the character well the benchmark program will increase the visual complexity of the display.
Human-Computer Interaction
Unleashing Artificial Cognition: Integrating Multiple AI Systems
In this study, we present an innovative fusion of language models and query analysis techniques to unlock cognition in artificial intelligence.
Recent Advances and New Frontiers in Spiking Neural Networks
In recent years, spiking neural networks (SNNs) have received extensive attention in brain-inspired intelligence due to their rich spatially-temporal dynamics, various encoding methods, and event-driven characteristics that naturally fit the neuromorphic hardware.
A Bayesian dynamic stopping method for evoked response brain-computer interfacing
As brain-computer interfacing (BCI) systems transition from assistive technology to more diverse applications, their speed, reliability, and user experience become increasingly important.
Human-Computer Interaction
