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  1. 1
    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning

    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

    Published 2024
    “…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. …”
    Conference Paper
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  2. 2
    Raspberry Pi-Based Finger Vein Recognition System Using PCANet

    Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

    Published 2018
    “…For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. An enhancement version for kNN algorithm, k-General Nearest Neighbours (kGNN) have been proposed at initial stage. …”
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    Monograph
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  3. 3
    Image Splicing Detection With Constrained Convolutional Neural Network

    Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

    Published 2019
    “…It is shown that CNN with constrained convolution algorithm can be used as a general image splicing detection task.…”
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    Thesis
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  4. 4
    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
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    Thesis
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  5. 5
    Routing performance enhancement in hierarchical torus network by link-selection algorithm

    Routing performance enhancement in hierarchical torus network by link-selection algorithm by Rahman, M.M. Hafizur, Horiguchi, Susumu

    Published 2005
    “…We evaluate the dynamic communication performance of an HTN using dimension-order routing and link-selection algorithms under various traffic patterns. …”
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  6. 6
    Dynamic communication performance enhancement in hierarchical torus network by selection algorithm

    Dynamic communication performance enhancement in hierarchical torus network by selection algorithm by Rahman, M.M. Hafizur, Sato, Yukinori, Inoguchi, Yasushi

    Published 2012
    “…The dynamic communication performances of an HTN is evaluated by using dimension-order routing and proposed adaptive routing algorithms under various traffic patterns. …”
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  7. 7
    Adaptive routing algorithms and implementation for TESH network

    Adaptive routing algorithms and implementation for TESH network by Miura, Yasuyuki, Kaneko, Masahiro, Rahman, M.M. Hafizur, Watanabe, Shigeyoshi

    Published 2013
    “…It is found that the communication performance of a TESH network using these adaptive algorithms is better than when the dimension-order routing algorithm is used.…”
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  8. 8
    Butterfly traffic pattern in selection algorithm on hierarchical torus network

    Butterfly traffic pattern in selection algorithm on hierarchical torus network by Rahman, M.M. Hafizur, Akhand, M. A. H, Shill, P.C., Inoguchi, Yasushi

    Published 2015
    “…In this paper, we have evaluated the dynamic communication performances of an HTN is evaluated by using dimension-order routing and LS+CS algorithm under butterfly traffic pattern. …”
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    Proceeding Paper
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  9. 9
    Analysis randomness properties of basic components of SNOW 3G cipher in mobile systems

    Analysis randomness properties of basic components of SNOW 3G cipher in mobile systems by Jassim, Khalid Fadhil, Alshaikhli, Imad Fakhri Taha

    Published 2016
    “…SNOW 3G is a stream cipher algorithm used as encryption algorithm in third generation mobile phone technology (3G-UMTS). …”
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  10. 10
    Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm

    Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm by Fatma Susilawati, Mohamad, Mumtazimah, Mohamad, Sarhan, AlDuais

    Published 2020
    “…We created the dynamic learning rate and dynamic momentum factor for increasing the efficiency of the algorithm. …”
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  11. 11
    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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  12. 12
    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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  13. 13
    Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar

    Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar by Ja'afar, Nur Shahirah

    Published 2021
    “…These algorithms were developed by using prewar shophouses dataset from 2004 until 2018 based on factors of heritage properties. …”
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  14. 14
    High performance hierarchical torus network under matrix transpose traffic patterns

    High performance hierarchical torus network under matrix transpose traffic patterns by Rahman, M.M. Hafizur, Susumu, Horiguchi

    Published 2004
    “…In this paper, we present a deadlock-free routing algorithm for the HTN using virtual channels and evaluate the network’s dynamic communication performance under matrix transpose traffic, using the proposed routing algorithm. …”
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    Proceeding Paper
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  15. 15
    Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding

    Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding by Mahmoud, Omer, Anwar, Farhat, Salami, Momoh Jimoh Emiyoka

    Published 2007
    “…One of the essential factors that affect the performance of Artificial Neural Networks is the learning algorithm. …”
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  16. 16
    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus

    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

    Published 2003
    “…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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  17. 17
    Optimization of chest X-ray exposure factors using machine learning algorithm

    Optimization of chest X-ray exposure factors using machine learning algorithm by Hamd, Zuhal Y., Alrebdi, H.I., Osman, Eyas G., Awwad, Areej, Alnawwaf, Layan, Nashri, Nawal, Alfnekh, Rema, Khandaker, Mayeen Uddin *

    Published 2023
    “…In this study, the chest X-ray exposure factors for 178 patients with different body mass index (BMI) values have been analyzed using the Python Machine Learning algorithm. …”
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  18. 18
    A bayesian network approach to identify factors affecting learning of Additional Mathematics

    A bayesian network approach to identify factors affecting learning of Additional Mathematics by Ong, Hong Choon, Kumarenthiran A/L Chandrasekaran

    Published 2015
    “…Constraint-based algorithms and score-based algorithms are used to generate the networks into several categories to compare and identify the strong relationships among the factors that affect the students’ learning of the subject. …”
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  19. 19
    Evaluation of stereo matching algorithms and dynamic programming for 3D triangulation

    Evaluation of stereo matching algorithms and dynamic programming for 3D triangulation by Teo, Chee Huat, Manap, Nurulfajar

    Published 2015
    “…The stereo matching algorithms that we applied for experimental purpose are basic block matching, sub-pixel accuracy and dynamic programming. …”
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    Book Chapter
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  20. 20
    Evaluation Of Stereo Matching Algorithms And Dynamic Programming For 3D Triangulation

    Evaluation Of Stereo Matching Algorithms And Dynamic Programming For 3D Triangulation by Teo , Chee Huat, Abd Manap, Nurulfajar

    Published 2014
    “…The stereo matching algorithms that we applied for experimental purpose are basic block matching, sub-pixel accuracy and dynamic programming. …”
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