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EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method
Published 2018“…Standardized Low Resolution Tomography (sLORETA) andWeighted Minimum Norm (WMN) are linear distributed inverse solutions which lead up to zero localization error using noise-free EEG, state-of-the-art feature extractor and realistic head model. …”
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Thesis -
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Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization
Published 2018“…High accuracy results of proposed algorithm using non-invasive and low-resolution EEG provide the potential of using this work for pre-surgical evaluation towards epileptogenic zone localization in clinics.…”
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Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization
Published 2018“…High accuracy results of proposed algorithm using non-invasive and low-resolution EEG provide the potential of using this work for pre-surgical evaluation towards epileptogenic zone localization in clinics.…”
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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Fatigue State Detection Through Multiple Machine Learning Classifiers Using EEG Signal
Published 2023“…The classification accuracy using Decision Tree for four classes and two classes were achieved at 88.61% and 88.21% respectively, which can make this EEG-based technology a practical and dependable solution for real-time applications.…”
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Bayesian Framework based Brain Source Localization Using High SNR EEG Data
Published 2019“…The brain signals are recorded through neuroimaging techniques such as MEG, EEG, fMRI and PET etc. Nevertheless, when EEG signals are used to reconstruct the active brain sources, then its termed as EEG source localization. …”
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Recent Trends and Open Challenges in EEG based Brain-Computer Interface Systems
Published 2019“…In this paper, we have tried to mention some critical issues of EEG based BCI system including EEG modalities, EEG acquisition, signal processing algorithm and performance evaluation. …”
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Fuzzification of epileptic data: an application for prediction and identification of partial seizure
Published 2013“…Hence in this proposed system, we introduce fuzzification of epileptic EEG data using fuzzy logic interface to classify partial seizure EEG signals from the normal EEG. …”
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13
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique
Published 2016“…The IncFRNN algorithm is able to control the size of training pool using predefined window size threshold. …”
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Fine-tuning approach in metaheuristic algorithm to prolong wireless sensor networks nodes lifetime
Published 2022“…A set of simulations has been performed using MATLAB R2018b on the proposed solution, namely the energy efficient of genetic (EEG) algorithm and has revealed that the solution outperforms the network lifetime and cluster head load of the existing solution.…”
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Automatic microsleep detection based on KNN classifier utilizing selected and effective EEG channels
Published 2024“…The study revealed that the suggested approach achieved a classification accuracy of 98.28% within a time window of 0.5 seconds to detect microsleep using EEG signal. The exceptional effectiveness of the given system can be efficiently utilized in detecting microsleep using EEG signal.…”
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Mental Stress Classification Among Higher Education Students In Malaysia From Electroencephalogram (Eeg) Using Convolutional Neural Network With Modified Stochastic Gradient D...
Published 2024“…The 1D CNN model also demonstrated high sensitivity and specificity, making it a robust solution for EEG-based stress detection.…”
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Parameter tuning for enhancing inter-subject emotion classification in four classes for vr-eeg predictive analytics
Published 2020“…The following research describes the potential in classifying emotions using wearable EEG headset while using a virtual environment to stimulate the responses of the users. …”
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Ant colony optimization algorithm for load balancing in grid computing
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