Search Results - (( pattern extraction path algorithm ) OR ( parallel visualization learning algorithm ))

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    Grid portal technology for web based education of parallel computing courses, applications and researches by Alias, Norma, Islam, Md. Rajibul, Mydin, Suhaimi, Hamzah, Norhafiza, Safiza Abd. Ghaffar, Zarith, Satam, Noriza, Darwis, Roziha

    Published 2009
    “…These courses will actively engage the students in exploring the concepts of the development the parallel algorithm in visualizing the grand challenge applications of mathematical problems. …”
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    Conference or Workshop Item
  4. 4

    Animal voice recognition for identification (ID) detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

    Published 2011
    “…While the voice pattern classification will be done by using DTW algorithm. …”
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  5. 5

    Dog voice identification (ID) for detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

    Published 2012
    “…While the voice pattern classification will be done by using DTW algorithm. …”
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    NN with DTW-FF Coefficients and Pitch Feature for Speaker Recognition by Sudirman, Rubita, Salleh, Sh-Hussain, Salleh, Shaharuddin

    Published 2006
    “…This paper proposes a new method to extract speech features in a warping path using dynamic programming (DP). …”
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    Article
  7. 7

    Local DTW coefficients and pitch feature for back-propagation NN digits recognition by Sudirman, R., Salleh, Shahruddin Hussain, Salleh, Sh-Hussain

    Published 2006
    “…This paper presents a method to extract existing speech features in dynamic time warping path which originally was derived from LPC. …”
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    Conference or Workshop Item
  8. 8

    Local DTW Coefficients and Pitch Feature for Back-Propagation NN Digits Recognition by Sudirman, Rubita, Salleh, Sh-Hussain, Salleh, Shaharuddin

    Published 2006
    “…This paper presents a method to extract existing speech features in dynamic time warping path which originally was derived from LPC. …”
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    Conference or Workshop Item
  9. 9

    Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network by Ahmad Afif, Mohd Faudzi

    Published 2012
    “…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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    Thesis
  10. 10

    Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network by Ahmad Afif, Mohd Faudzi

    Published 2012
    “…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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    Undergraduates Project Papers
  11. 11

    A novel neuroscience-inspired architecture: for computer vision applications by Hassan, Marwa Yousif, Khalifa, Othman Omran, Abu Talib, Azhar, Olanrewaju, Rashidah Funke, Hassan Abdalla Hashim, Aisha

    Published 2016
    “…The theory behind deep learning, the human visual system was investigated and general principles of how it functions are extracted. …”
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    Proceeding Paper
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    Advances in materials informatics: A review by Sivan, Dawn, Kumar, K. Satheesh, Aziman, Abdullah, Raj, Veena, Izan Izwan, Misnon, Ramakrishna, Seeram, Jose, Rajan

    Published 2024
    “…Conventional ML models are simple and interpretable, relying on statistical techniques and algorithms to learn patterns and make predictions with limited data. …”
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    Article
  14. 14

    Investigating computational thinking among primary school students in Terengganu using visual programming by Osmanullrazi, Abdullah

    Published 2022
    “…Recent studies have shown that visual programming is one of the efficient tools to develop CT skills. …”
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    Thesis
  15. 15

    A hybrid environment control system combining EMG and SSVEP signal based on brain-computer interface technology by Rashid, Mamunur, Bari, Bifta Sama, Norizam, Sulaiman, Mahfuzah, Mustafa, Md Jahid, Hasan, Islam, Md Nahidul, Naziullah, Shekh

    Published 2021
    “…The feature in terms of the common spatial pattern (CSP) has been extracted from four classes of SSVEP response, and extracted feature has been classified using K-nearest neighbors (k-NN) based classification algorithm. …”
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    Article