Search Results - (( simulation classification cell algorithm ) OR ( java applications usage algorithm ))

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    An Adaptive Fuzzy Contrast Enhancement Algorithm with Details Preserving by Jing, Rui Tang, Mat Isa, Nor Ashidi

    Published 2014
    “…In addition, the experiments using cervical cell images and HEp-2 cell images showed great potential of the AFCEDP technique as a technique for enhancing medical microscopic images.…”
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    Article
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    An Effective Fast Searching Algorithm for Internet Crawling Usage by Chia, Zhen Hon, Nor Azhar, Ahmad

    Published 2016
    “…The search algorithm is a crucial part in any internet applications. …”
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    Conference or Workshop Item
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    Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural by Saidin, Mohammad Norrish

    Published 2006
    “…The topic of this project is classification of cervical cells into normal and abnormal using 2 group discriminant analysis and neural network. …”
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    Monograph
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    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…The experimental result shows that using Java 2, this method improves the speed of PrefixSpan up to almost two orders of magnitude as well as the memory usage to more than one order of magnitude.…”
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    Conference or Workshop Item
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    Computational analysis of biological data: Where are we? by Soreq, Lilach, Mohamed, Wael Mohamed Yousef

    Published 2024
    “…Using computational modeling, classification algorithms can be applied to microarray and RNA sequencing data (such as hierarchical clustering - HCL, t-SNE and principal component analysis - PCA), and high-resolution images can be generated based on the analyzed data and patient samples. …”
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    Book Chapter
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    Hand motion detection from EMG signals by using ANN based classifier for human computer interaction by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2011
    “…The simulation results show that the designed network is able to recognize hand movements with satisfied classification efficiency in average of 88.4%. …”
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    Proceeding Paper