Litcius/Paper detail

A new training approach for deep learning in EEG biometrics using triplet loss and EMG-driven additive data augmentation

Sherif Nagib Abbas Seha, Dimitrios Hatzinakos

2022Neurocomputing11 citationsDOI

Topics & Concepts

Computer scienceElectroencephalographyBiometricsArtificial intelligenceSpeech recognitionBrain–computer interfaceSession (web analytics)Pattern recognition (psychology)Deep learningNoise (video)Artificial neural networkMachine learningPsychiatryImage (mathematics)World Wide WebPsychologyEEG and Brain-Computer InterfacesNeuroscience and Neural EngineeringMuscle activation and electromyography studies
A new training approach for deep learning in EEG biometrics using triplet loss and EMG-driven additive data augmentation | Litcius