Search Results - (( brain computer support algorithm ) OR ( java implication based algorithm ))

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  1. 1
    Detection of eye movements based on EEG signals and the SAX algorithm

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

    Published 2018
    “…In this paper, we propose the Brain-Computer Interface (BCI) approach as a potential technique. …”
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  2. 2
    Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion

    Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion by Zafar, R., Dass, S.C., Malik, A.S.

    Published 2017
    “…However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types of images. …”
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  3. 3
    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network

    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…MVPA uses machine learning algorithms to classify different brain states and helps in prediction during the task. …”
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  4. 4
    P300 detection of brain signals using a combination of wavelet transform techniques

    P300 detection of brain signals using a combination of wavelet transform techniques by Motlagh, Farid Esmaeili

    Published 2012
    “…Wavelet transform (WT), student’s two-sample t-statistic (T-Test) and support vector machines (SVM) used in designing the algorithms. …”
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  5. 5
    A robust technique of brain MRI classification using color features and k-nearest neighbor algorithm

    A robust technique of brain MRI classification using color features and k-nearest neighbor algorithm by Fayaz, Muhammad, Shah, Abdul Salam, Wahid, Fazli, Shah, Asadullah

    Published 2016
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  6. 6
    Fuzzy support vector machine based fall detection method for traumatic brain injuries: A new systematic approach of combining fuzzy logic with support vector machine to achieve higher accuracy in fall detection system

    Fuzzy support vector machine based fall detection method for traumatic brain injuries: A new systematic approach of combining fuzzy logic with support vector machine to achieve hig... by Harum, Norharyati, Khalil, Mohamad Kchouri, Obeid, Ali, Hazimeh, Hussein

    Published 2022
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  7. 7
    Wavelet-based compression of medical images: Filter-bank selection and evaluation

    Wavelet-based compression of medical images: Filter-bank selection and evaluation by Saffor, A., Bin Ramli, A.R., Ng, K.H.

    Published 2003
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  8. 8
    Synaptogenesis based bio-inspired NoC fault tolerant interconnects

    Synaptogenesis based bio-inspired NoC fault tolerant interconnects by Sethi, Muhammad Athar Javed, Hussin, Fawnizu Azmadi, Hamid, Nor Hisham

    Published 2013
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  9. 9
    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition

    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

    Published 2019
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  10. 10
    Optimization of least squares support vector machine technique using genetic algorithm for electroencephalogram multi-dimensional signals

    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
    “…Human-computer intelligent interaction (HCII) is a rising field of science that aims to refine and enhance the interaction between computer and human. …”
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  11. 11
    Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks

    Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks by Ayomide, Kabirat Sulaiman, Mohd Aris, Teh Noranis, Zolkepli, Maslina

    Published 2023
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  12. 12
    Early Detection Of ADHD Among Children Using Machine Learning

    Early Detection Of ADHD Among Children Using Machine Learning by Nur Atiqah, Kamal

    Published 2023
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  13. 13
    Classification of Healthy Condition and Depression using functional Near Infrared Spectroscopy (fNIRS)

    Classification of Healthy Condition and Depression using functional Near Infrared Spectroscopy (fNIRS) by Mohd, Murni Athirah

    Published 2018
    “…In this study, fNIRS has been chosen as a neuroimaging modality to establish a new biomarker for Brain-Computer Interface (BCI). The aim of this project is to investigate if fNIRS showing the haemodynamic of brain activity can help distinguish the condition of the individual either healthy condition and depression. …”
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    Final Year Project
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  14. 14
    Optimizing kindergarten schedule using : graph coloring / Nur Nabilah Salleh Muner

    Optimizing kindergarten schedule using : graph coloring / Nur Nabilah Salleh Muner by Salleh Muner, Nur Nabilah

    Published 2019
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    Research Reports
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  15. 15
    Prediction of Alzheimer disease using improved MMSE ensemble regressor based on magnetic resonance images

    Prediction of Alzheimer disease using improved MMSE ensemble regressor based on magnetic resonance images by Farzan, Ali

    Published 2015
    “…Nowadays, it is obvious that onset of the disease can be even decades before manifestation of the symptoms and it can be revealed by investigating the brain structures. Early prognosing of Alzheimer’s disease by analyzing brain MR images and inspecting effect of it on brain structures is a hard task. …”
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  16. 16
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  17. 17
    Evaluating the effectiveness of time-domain features for motor imagery movements using SVM

    Evaluating the effectiveness of time-domain features for motor imagery movements using SVM by Khorshidtalab, Aida, Salami, Momoh Jimoh Emiyoka, Hamedi , Mahyar

    Published 2012
    “…In this work, in order to have less computational complexity, time-domain algorithms are employed to motor imagery signals. …”
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  18. 18
    Wink based facial expression classification using machine learning approach

    Wink based facial expression classification using machine learning approach by Rashid, Mamunur, Norizam, Sulaiman, Mahfuzah, Mustafa, Bari, Bifta Sama, Sadeque, Md Golam, Hasan, Md Jahid

    Published 2020
    “…Fast Fourier transform and the sample range have been computed to extract the features. The extracted features have been classified with the help of different machine learning algorithms. …”
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  19. 19
    Single classifer vs. ensemble machine learning approaches for mental health prediction

    Single classifer vs. ensemble machine learning approaches for mental health prediction by Jetli Chung, Jason Teo

    Published 2023
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  20. 20
    Discrete wavelet packet transform for electroencephalogram-based emotion recognition in the valence-arousal space

    Discrete wavelet packet transform for electroencephalogram-based emotion recognition in the valence-arousal space by Ahmad, Farzana Kabir, Olakunle, Oyenuga Wasiu

    Published 2015
    “…Human emotion recognition is the key step toward innovative human-computer interactions.The advanced in computational algorithms and techniques has recently offered the promising results in recognizing human emotion.Recently, Electroencephalogram (EEG) has been shown as an effective way in identifying human emotion since it records the brain activity of human and can hardly be deceived by voluntary control.However, due to the non-linearity, non-stationary, and chaotic nature of the EEG signals, it is difficult to be examined and has been an extensive research area in the present years. …”
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