Search Results - (( ((using eeg) OR (using deep)) problem algorithm ) OR ( java simulation optimization algorithm ))

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  1. 1

    An Investigation to Detect Driver Drowsiness from Eye blink Artifacts Using Deep Learning Models by Egambaram, A., Badruddin, N.

    Published 2022
    “…The eye blink artifacts and their features are extracted from EEG signals via the BLINKER algorithm. The deep learning classifiers, multilayer perceptron (MLP) and Recurrent Neural Network with Long-Short-Term-Memory (RNN-LSTM) are trained, validated, and tested to confirm if the eye blink artifacts can be used as an indicator of drowsiness. …”
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    Conference or Workshop Item
  2. 2

    Epileptic seizure detection from electroencephalogram (EEG) signals using linear graph convolutional network and DenseNet based hybrid framework by Jibon, Ferdaus Anam, Miraz, Mahadi Hasan, Khandaker, Mayeen Uddin *, Rashdan, Mostafa, Salman, Mohammad, Tasbir, Alif, Nishar, Nazibul Hasan, Siddiqui, Fazlul Hasan

    Published 2023
    “…The Stockwell transform (S-transform) is used to preprocess from the raw EEG signal and then group the resulting matrix into time-frequency blocks as inputs for the LGCN to use for feature selection and after the Densenet uses for classification. …”
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    Article
  3. 3

    A robust framework epileptic seizures classification based on lightweight structure deep convolutional neural network and wavelet decomposition by Nazanin Nemati, Saeed Meshgini, Ali Farzamnia

    Published 2020
    “…Using the EEG signals obtained from the CHEG-MIT Scalp EEG database, the implementation in the desired model is performed and the results show that the proposed model has the best response in detecting the disease from the sample signal and with the highest level of certainty to follow. …”
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    Conference or Workshop Item
  4. 4

    Sleep arousal events detection using PNN-GBMO classifier based on EEG and ECG signals: A hybrid-learning model by Afsoon Badiei, Saeed Meshgini, Ali Farzamnia

    Published 2020
    “…In this paper, the detection of arousal events is performed using an automatic analysis of EEG and ECG signals. …”
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    Conference or Workshop Item
  5. 5

    Multivariate EEG signal processing techniques for the aid of severely disabled people by Ibrahimy, Muhammad Ibn, Ibrahimy, Ahmad Ibn

    Published 2022
    “…Many studies have revealed the correlation of mental tasks with the EEG signals for actual or fictional movements. However, the performance of Brain Computer Interface (BCI) using EEG signal is still below enough to assist any disabled people. …”
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    Article
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    Applying SAX-based time series analysis to classify EEG signal using a COTS EEG device by Shanmuga, Pillai A/L Murutha Muthu

    Published 2021
    “…One of the proposals that could help solve this problem is the use of brain-computer interface (BCI)s. …”
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    Thesis
  9. 9

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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    Thesis
  10. 10

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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    Monograph
  11. 11

    Detection of eye movements based on EEG signals and the SAX algorithm by Shanmuga, P. M. M., Lau, Sian Lun *, Jou, Chichang.

    Published 2018
    “…The patients may use a portable electroencephalography (EEG) device to give instruction to a computing device via eye movements. …”
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    Conference or Workshop Item
  12. 12
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    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

    Published 2017
    “…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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    Thesis
  14. 14
  15. 15

    Optimization of least squares support vector machine technique using genetic algorithm for electroencephalogram multi-dimensional signals by Ahmad, Farzana Kabir, Al-Qammaz, Abdullah Yousef Awwad, Yusof, Yuhanis

    Published 2016
    “…Discrete wavelet packet transform (DWPT) has been used to extract EEG signals feature and ultimately 204,800 features from 32 subject-independent have been obtained. …”
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    Article
  16. 16

    Comparison on performance of adaptive algorithms for eye blinks removal in electroencephalogram by Abd Rahman, Faridah, Othman, Mohd Fauzi, Hamzah, Mohd Ilham Rusydan Hamzah

    Published 2018
    “…To overcome this problem, an algorithm to automatically detect and remove the artifacts from EEG signals is highly desirable. …”
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    Proceeding Paper
  17. 17

    EEG-based brain source localization using visual stimuli by Jatoi, M.A., Kamel, N., Malik, A.S., Faye, I., Bornot, J.M., Begum, T.

    Published 2016
    “…FDM is used for head modelling to solve forward problem. …”
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    Article
  18. 18

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
    Review
  19. 19

    Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification by Al-Sharhan, Salah, Bimba, Andrew

    Published 2019
    “…Thus, we propose an adaptive multi-parent crossover Genetic Algorithm (GA) for optimizing the features used in classifying epileptic seizures. …”
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    Article
  20. 20

    Bayesian Framework based Brain Source Localization Using High SNR EEG Data by Jatoi, M.A., Kamel, N., Gaho, A.A., Dharejo, F.A.

    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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    Conference or Workshop Item