Showing 2,001 - 2,020 results of 2,101 for search 'patterns research algorithms', query time: 0.17s Refine Results
  1. 2001

    Exploring the process—structure–property relationship of nylon aramid 3D printed composites and parameter optimization using supervised machine learning techniques by Mohammed Raffic Noor Mohamed, Ganesh Babu Karuppiah, Dharani Kumar Selvan, Rajasekaran Saminathan, Shubham Sharma, Shashi Prakash Dwivedi, Sandeep Kumar, Mohamed Abbas, Dražan Kozak, Jasmina Lozanovic

    Published 2025-02-01
    “…The main goals of this research are to identify the significant input parameters using supervised machine learning methods and investigate the relationship between the process, structure, and properties of components created using fused deposition modeling utilizing nylon aramid composite filaments. …”
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    Article
  2. 2002

    Exploring the potential of machine learning and magnetic resonance imaging in early stroke diagnosis: a bibliometric analysis (2004–2023) by Jian-cheng Lou, Xiao-fen Yu, Jian-jun Ying, Da-qiao Song, Wen-hua Xiong

    Published 2025-03-01
    “…The most notable research hotspots currently are the optimal selection of neural imaging markers and the most suitable machine learning algorithm models.…”
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    Article
  3. 2003
  4. 2004
  5. 2005
  6. 2006

    Investigation of the ecology of winter plankton of Lake Baikal using complex instrumental methods by E. Yu. Naumova, T. P. Rzhepka, M. M. Makarov, A. S. Olshukov, K. M. Kucher, M. Z. Magomedova, E. S. Troitskaya

    Published 2021-10-01
    “…The obtained field data will make it possible to further improve the pattern recognition algorithm in the software of the holographic installation for the specific conditions of Lake Baikal. …”
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    Article
  7. 2007

    Rock blasting evaluation - image recognition method based on deep learning by Haibao YI, Aixiang Wu, Xiliang Zhang

    Published 2025-07-01
    “…Research has shown that the half-hole rate derived from manual statistics and image recognition is 68.16% and 67.15%, respectively, with an average error of 1.49%. …”
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    Article
  8. 2008
  9. 2009

    An Approach for Predicting the Shape and Size of a Buried Basic Object on Surface Ground Penetrating Radar System by Nana Rachmana Syambas

    Published 2012-01-01
    “…However, the output target is only hyperbolic representation. This research develops a system to identify a buried object on surface GPR based on decision tree method. …”
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    Article
  10. 2010

    Advanced Human Pose Estimation and Event Classification Using Context-Aware Features and XGBoost Classifier by Wasim Wahid, Aisha Ahmed AlArfaj, Ebtisam Abdullah Alabdulqader, Touseef Sadiq, Hameedur Rahman, Ahmad Jalal

    Published 2024-01-01
    “…Despite many surveys, a comprehensive review of HPE, especially with recent deep learning innovations, is still needed. Our research addresses this by proposing a novel HPE and SEC system. …”
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    Article
  11. 2011

    Sensor Fusion for Enhancing Motion Capture: Integrating Optical and Inertial Motion Capture Systems by Hailey N. Hicks, Howard Chen, Sara A. Harper

    Published 2025-07-01
    “…This study aimed to create and evaluate an optimization-based sensor fusion algorithm that combines Optical Motion Capture (OMC) and Inertial Motion Capture (IMC) measurements to provide a more efficient and reliable gap-filling process for OMC measurements to be used for future research. …”
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    Article
  12. 2012

    Hybrid beamforming for ISAC based on mmWave cell-free MIMO by DUO Lin, YANG Xin, REN Yong, XU Boyu

    Published 2024-10-01
    “…Two kinds of power constraints are considered in the study, and the improved orthogonal matching pursuit algorithm and the Riemann conjugate gradient algorithm are used for optimization. …”
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    Article
  13. 2013

    Integration Method with Backpropagation by Nidhal AL-Assady, Jamal Majeed, Shahbaa Khaleel

    Published 2005-06-01
    “…In this research, a new method is discovered (combined method) to accelerate the backpropagation network by using the expected values of source units for updating weights, we mean the expected value of unit by the sum of the output of the unit and its error term multiplied by the factor Beta to accelerate the algorithm and also adjust the value of learning coefficient continuously if the value of energy function E decreases the learning rate is increased by a factor , if the value of the energy function E increases , the value of the learning rate is decreased by a factor . …”
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    Article
  14. 2014
  15. 2015

    A Multifrequency Brain Network-Based Deep Learning Framework for Motor Imagery Decoding by Juntao Xue, Feiyue Ren, Xinlin Sun, Miaomiao Yin, Jialing Wu, Chao Ma, Zhongke Gao

    Published 2020-01-01
    “…The filter bank common spatial pattern (FBCSP) algorithm filters the MI-based EEG signals in the spatial domain to extract features. …”
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    Article
  16. 2016

    Promotion or inhibition? Exploring the influence of the digital economy on urban-rural integration: A case study of yellow River basin by Mingxi Zhou, Fuyou Guo, Yongsheng Sun, Jiamin Ren, Xuebo Zhang

    Published 2024-12-01
    “…Using the Yellow River Basin as an empirical case study area, the projection pursuit model, simulated annealing algorithm and spatial Durbin model were employed to explore the impact of the digital economy on urban-rural integration in the Yellow River Basin from 2011 to 2021. …”
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    Article
  17. 2017

    Precision neuropsychology in the area of AI by Astri J. Lundervold

    Published 2025-05-01
    “…The paper also addresses critical implementation challenges: ethical considerations including algorithmic bias and data privacy; balancing quantitative AI analytics with qualitative clinical expertise to avoid reductionism; and developing new competencies for neuropsychologists to effectively integrate AI in their research and clinical work. …”
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    Article
  18. 2018

    Effects of urban sprawl on land use change in the peripheral villages of Tehran metropolis (case study: Tehran-Damavand axis) by ِAshkan Mohammadi, Naser Shafiei Sabet, Alireza Shakiba

    Published 2019-12-01
    “…After that, the supervised classification operation was monitored by the SVM algorithm and the detection and determination of the sprawl pattern in the study area. …”
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    Article
  19. 2019

    Characteristics of pore-fracture structure and three-dimensional spatial distribution differences in deep and shallow coal reservoirs: A case study of Junggar Basin by WANG Pengxiang, ZHANG Zhou, YU Wanying, ZOU Qiang, YANG Zhengtao

    Published 2025-04-01
    “…A pore network model for the samples was established using the maximal sphere algorithm to analyze the distribution pattern, morphology, and three-dimensional structural development of the connected pores and fractures. …”
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    Article
  20. 2020