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  1. Home
  2. Volume 10, Issue 2
  3. Author

Online ISSN: 2515-8260

Volume10, Issue2

IMAGE PROCESSING USING MACHINE LEARNING

    Dr.M.Rajaiah,Dr.P.Chandrakanth,Ms.P.Akanksha,Ms.N.Neeraja,Ms.K.Bhuvaneswari,Mr.P.Venkata Subrahmanyam .

European Journal of Molecular & Clinical Medicine, 2023, Volume 10, Issue 2, Pages 322-330

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Abstract

Much attention has been paid to the usage of handwritten mathematical equations and symbols, including pattern recognition industry consolidation Using a novel and sophisticated algorithm, it is now possible to identify the handwritten characters, a more diverse variety of handwritten digits is now visible. A number of machine learning algorithms, including conventional Neural Networks, Support Vector Machines, and Multilayer Perception. Finding the most effective and efficient approach for pattern recognition is the key goal or objective. Paper displays the accuracy of various classification methods varies. The Bayesian Network makes a "rough" classification of a binary image. The use of neural networks for classification contents.
Keywords:
    pattern recognition digit recognition machine learning algorithms neural network classification algorithms
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(2023). IMAGE PROCESSING USING MACHINE LEARNING. European Journal of Molecular & Clinical Medicine, 10(2), 322-330.
Dr.M.Rajaiah,Dr.P.Chandrakanth,Ms.P.Akanksha,Ms.N.Neeraja,Ms.K.Bhuvaneswari,Mr.P.Venkata Subrahmanyam .. "IMAGE PROCESSING USING MACHINE LEARNING". European Journal of Molecular & Clinical Medicine, 10, 2, 2023, 322-330.
(2023). 'IMAGE PROCESSING USING MACHINE LEARNING', European Journal of Molecular & Clinical Medicine, 10(2), pp. 322-330.
IMAGE PROCESSING USING MACHINE LEARNING. European Journal of Molecular & Clinical Medicine, 2023; 10(2): 322-330.
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