NUST Institutions Library Catalogue catalog › Details for: Genetic Algorithm based Optimal Feature Selection for Hybrid EEG-EOG, EEG-EMG and EEG-fNIRS for BCI /

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Genetic Algorithm based Optimal Feature Selection for Hybrid EEG-EOG, EEG-EMG and EEG-fNIRS for BCI / NIDA MATEEN

TextIslamabad: SMME- NUST. 2021Description: 132p. ; Soft Copy, 30cmSubject(s): MS Robotics and Intelligent Machine EngineeringDDC classification: 629.8 Online resources: Click here to access online

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Item type	Current location	Home library	Shelving location	Call number	Status	Date due	Barcode	Item holds
Thesis	School of Mechanical & Manufacturing Engineering (SMME)	School of Mechanical & Manufacturing Engineering (SMME)	Thesis	629.8 (Browse shelf)	Available		SMME-TH-573

Total holds: 0

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Previous	629.8 Analyzing Human Behavior and Memory Activities using Deep Learning for BMI /	629.8 An integrated EEG-fNIRS-based Vector-Phase Analysis for early hemodynamic response: Applications to BCI /	629.8 Maritime Accident Analysis and AI based HCD IoOT Larch for Operator Vigilance and Cognition /	629.8 Genetic Algorithm based Optimal Feature Selection for Hybrid EEG-EOG, EEG-EMG and EEG-fNIRS for BCI /	629.8 Classification of Cancer using Epigenetic Markers in the Head and Neck /	629.8 A portable Spatially Resolved Functional Near Infrared Spectroscopy system for 3D Hemodynamic Imaging /	629.8 Fruits Category Identification and Infected Part Detection using Deep Learning /	Next

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