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  1. 1

    Stereo matching algorithm using deep learning and edge-preserving filter for machine vision by Abd Gani, Shamsul Fakhar, Miskon, Muhammad Fahmi, Hamzah, Rostam Affendi, Hamid, Mohd Saad, Kadmin, Ahmad Fauzan, Herman, Adi Irwan

    Published 2024
    “…This paper proposes a hybrid method of a stereo matching algorithm with the goal of generating an accurate disparity map critical for applications such as 3D surface reconstruction and robot navigation to name a few. …”
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    Article
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    Static hand sign recognition using linear projection methods by Gamage, Nuwan, Chow, Kuang Ye, Akmeliawati, Rini

    Published 2000
    “…Successful shape matching algorithms/ methods has a high potential for a wide variety of practical applications. …”
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    Proceeding Paper
  4. 4

    Static hand sign recognition using linear projection methods by Gamage, Nuwan, Chow, Kuang Ye, Akmeliawati, Rini

    Published 2009
    “…Successful shape matching algorithms/ methods has a high potential for a wide variety of practical applications. …”
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    Proceeding Paper
  5. 5

    Neural Network Based Pattern Recognition in Visual Inspection System for Intergrated Circuit Mark Inspection by Sevamalai, Venantius Kumar

    Published 1998
    “…These algorithms could not compensate for the change or variation on the inspected parts dynamically. …”
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    Thesis
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    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…Traditional schema theory does not support Lamatckian learning, i.e, forcing the genetic representation to match the solution found by the learning algorithm. …”
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    Article
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    Tree-based machine learning in classifying reverse migration/ Azreen Anuar, Nur Huzeima Mohd Hussain and Hugh Byrd by Anuar, Azreen, Mohd Hussain, Nur Huzeima, Byrd, Hugh

    Published 2023
    “…The findings revealed that tree-based machine learning algorithms performed slightly better than linear-based algorithms in terms of accuracy of prediction, with an improvement of approximately 1%. …”
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    Article
  13. 13

    A new text-based w-distance metric to find the perfect match between words by Ali, M., Jung, L.T., Hosam, O., Wagan, A.A., Shah, R.A., Khayyat, M.

    Published 2020
    “…The k-NN algorithm is an instance-based learning algorithm which is widely used in the data mining applications. …”
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    Article
  14. 14

    Ensemble Dual Algorithm Using RBF Recursive Learning for Partial Linear Network by Md Akib, Afif, Saad, Nordin, Asirvadam, Vijanth

    Published 2011
    “…A new learning algorithm called the ensemble dual algorithm for estimating the mass-flow rate of the flow after leakage is proposed. …”
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    Book Section
  15. 15

    Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm by Jaber M.M., Yussof S., Elameer A.S., Weng L.Y., Abd S.K., Nayyar A.

    Published 2023
    “…Automation; Complex networks; Computational complexity; Deep learning; Image analysis; Medical imaging; Pattern matching; Pixels; Distribution pattern-matching rule; Distribution patterns; Gray wolf-optimized deep convolution network; Gray wolves; Learning patterns; Matching rules; Medical fields; Medical image analysis; Pattern matching algorithms; Pattern-matching; Convolution…”
    Article
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    Efficient 3D stereo vision stabilization for multi-camera viewpoints by Bhuiyan, Sharif Shah Newaj, Khalifa, Othman Omran

    Published 2019
    “…Tree algorithm helps to stabilize randomly positioned camera viewpoints in linear order. …”
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    Article
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    Image matching using relational graph representation by Lai, Chui Yen

    Published 2005
    “…Feature-based matching algorithm cannot tackle the problem of matching ambiguities easily. …”
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    Thesis
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    Pulse residual excited linear prediction by Shah, Asadullah, Shaikh, Muniba

    Published 2011
    “…Pulse Residual Excited Linear Prediction (PRELP) is a variant ofCELP encoding algorithm. …”
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    Book Chapter
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    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The experimental results demonstrate that the proposed algorithm is competitive compared to the state-of-the-art semi-supervised learning algorithms in terms of accuracy. …”
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    Thesis
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    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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    Thesis