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el 23(1):

Research Article

Use MOOC to learn image denoising techniques

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  • @ARTICLE{10.4108/eetel.4396,
        author={Ting Zhao},
        title={Use MOOC to learn image denoising techniques},
        journal={EAI Endorsed Transactions on e-Learning},
        volume={9},
        number={1},
        publisher={EAI},
        journal_a={EL},
        year={2023},
        month={11},
        keywords={MOOC, Image denoising, E-learning, Filtering Methods, Wavelet Transform, Deep Learning Approaches, Non-local Means Denoising},
        doi={10.4108/eetel.4396}
    }
    
  • Ting Zhao
    Year: 2023
    Use MOOC to learn image denoising techniques
    EL
    EAI
    DOI: 10.4108/eetel.4396
Ting Zhao1,*
  • 1: Henan Polytechnic University
*Contact email: zting@home.hpu.edu.cn

Abstract

This article focuses on using MOOCs to learn image denoising techniques. It begins with an introduction to the concept of MOOCs - these innovative online learning platforms that offer a wide range of courses across disciplines, providing convenient and affordable learning opportunities for a global audience. It then explains the characteristics of MOOC's wide coverage, high flexibility, and different from traditional education models. It then introduces the advantages of MOOCs: accessibility and inclusiveness (open to anyone with an Internet connection), cost-effectiveness (a cost-effective alternative, many courses available for free), flexibility and self-paced learning (the ability to learn at your own pace), a diverse curriculum and global expertise. Then the concept of image denoising is introduced - image denoising is a basic process of digital image processing, and the common denoising methods are described: filter method and the applicable range of various filters, the advantages and disadvantages of wavelet change, the advantages of deep learning method and the principle of non-local mean denoising technology. It then describes how MOOCs can help learn image denoising: integrating course content, getting expert guidance, hands-on exercises and projects, and community and peer communication. In addition, it introduces the challenges encountered by MOOCs: high dropout rate, quality and credibility of MOOCs, lack of interaction and humanization in traditional classrooms, accessibility. The relationship between E-learning and MOOC is also introduced – E-learning and MOOC play complementary roles in modern education. MOOC provide a structured, flexible, cost-effective environment and a transformative educational experience for learning about biological image denoising.

Keywords
MOOC, Image denoising, E-learning, Filtering Methods, Wavelet Transform, Deep Learning Approaches, Non-local Means Denoising
Received
2023-11-15
Accepted
2023-11-20
Published
2023-11-21
Publisher
EAI
http://dx.doi.org/10.4108/eetel.4396

Copyright © 2023 T. Zhao et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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