10.30495/ijm2c.2022.1936139.1224

An Introduction to the Application of Tensorial Manifold Learning Methods in the Digital Image Processing and Computer Vision

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  • Hamid Yazdani*1,
  • Ali Reza Shojaeifard2,
  1. Department of Mathematics, Payame Noor University (PNU), P.O. Box 19395-3697, Tehran, Iran
  2. Department of Mathematics, Faculty of Sciences, Imam Hossein Comprehensive University, Tehran, Iran.

Received: 22-07-2021

Accepted: 20-01-2022

Published in Issue 30-03-2022

Copyright (c) 2024 International Journal of Mathematical Modeling & Computations

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Yazdani, H., & Shojaeifard, A. R. (2022). An Introduction to the Application of Tensorial Manifold Learning Methods in the Digital Image Processing and Computer Vision. International Journal of Mathematical Modelling & Computations, 12(1), 27-35. https://doi.org/10.30495/ijm2c.2022.1936139.1224
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Abstract

Tensors as vector fields structures and manifolds as great geometrical-topological structures have many applications in the fields of big data analysis. Types of norms, metrics and scalable structures have been defined from various aspects. Nowadays, the hybrid methods between tensorial algorithms and manifold learning (MaL) methods have been attracted some attention. In image and signal processing, from image recovery to face recognition, these methods have appeared very excellent. According to our experiments by MATLAB R2021a, the hybrid algorithms are powerful other than algorithms based on the efficient popular parameters.
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