Search Results - (( java implication towards algorithm ) OR ( using sparse machine algorithm ))

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  1. 1

    Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field by Toh, Cheng Chuan

    Published 2018
    “…Theoretically,β and α is parameters that used to vary the NMF2D algorithm in order to yield high SDR value. …”
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    Thesis
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    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

    Published 2013
    “…In some cases, they are quite distant and sparseness. This uniqueness of Y-STR data has become problematic in partitioning the data using the existing partitional clustering algorithms. …”
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    A hybrid model based on constraint OSELM, adaptive weighted SRC and KNN for large-scale indoor localization by Gan, H., Khir, M.H.B.M., Witjaksono Bin Djaswadi, G., Ramli, N.

    Published 2019
    “…The understanding is that the original extreme learning machine (ELM) is less robust against noise, while sparse representation classification (SRC) and KNN suffer a high computational burden when using the over-complete dictionary. …”
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    DEVELOPMENT OF POINT CLOUD DESCRIPTORS FOR ROBUST 3D RECOGNITION by OSMAN ALI, YASIR SALIH

    Published 2015
    “…Among many surface descriptors proposed in the literature, orientation based descriptors are the most commonly used, however they are represented with large and sparse histograms. …”
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  13. 13

    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

    Published 2021
    “…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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  14. 14

    Auto-encoder variants for solving handwritten digits classification problem by Aamir, Muhammad, Mohd Nawi, Nazri, Mahdin, Hairulnizam, Naseem, Rashid, Zulqarnain, Muhammad

    Published 2020
    “…First, we introduce the conventional AE model and its different variant for learning abstract features from data by using a contrastive divergence algorithm. Second, we present the major differences among the following three popular AE variants: sparse AE (SAE), denoising AE (DAE), and contractive AE (CAE). …”
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  15. 15

    New Quarter-Sweep-Based Accelerated Over-Relaxation Iterative Algorithms and their Parallel Implementations in Solving the 2D Poisson Equation by Rakhimov, Shukhrat

    Published 2010
    “…The parallel strategies used in the new algorithms are based on the message latency minimization and processor-independent iterations.…”
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    Remote sensing technologies for unlocking new groundwater insights: a comprehensive review by Ibrahim, Abba, Wayayok, Aimrun, Mohd Shafri, Helmi Zulhaidi, Toridi, Noorellimia Mat

    Published 2024
    “…The evolution of the techniques analyses spans from empirical reliance on sparse point data to the assimilation of multi-platform satellite measurements using sophisticated machine learning algorithms. …”
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