Data Driven Processing Via Two-Dimensional Spearman Correlation Analysis (2D-SCA)

Muhammad Saddam Khokhar; Keyang Cheng; Misbah Ayoub; Zakria; Nida E. Rub

doi:10.1109/MACS48846.2019.9024798

Data Driven Processing Via Two-Dimensional Spearman Correlation Analysis (2D-SCA)

Muhammad Saddam Khokhar^*
, Keyang Cheng
, Misbah Ayoub
, Zakria
, Nida E. Rub

^*Corresponding author for this work

Jiangsu University
University of Electronic Science and Technology of China
National University of Computer and Emerging Sciences, Karachi

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

2 Citations (Scopus)

Abstract

This paper introduces an algorithm two-dimensional Spearman correlation analysis; the present algorithm is the extension of classical Spearman correlation analysis through algebraic solution for multivariate two-dimensional monotonic (linear or non-linear) multi-media datasets. In a way, two different images with nonlinearity challenges like different dimensions are processed with correspondence techniques such as reshaping images into 1D or vectors. Further, it can reduce dimension reduction along with quadratic algorithm complexity. Due to segmentation of matrices and tied rank ability of spearman correlation analysis. The implementation of proposed algorithm performs on four remarkable dataset. The results demonstration is helpful for researchers to choose finger image impression dataset with algorithm performance and sensors related techniques.

Original language	English
Title of host publication	2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-7
Number of pages	7
ISBN (Electronic)	978-1-7281-4957-8
ISBN (Print)	978-1-7281-4956-1
DOIs	https://doi.org/10.1109/MACS48846.2019.9024798
Publication status	Published - Dec 2019
Event	13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics, MACS 2019 - Karachi, Pakistan Duration: 14 Dec 2019 → 15 Dec 2019

Publication series

Name	MACS 2019 - 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics, Proceedings

Conference

Conference	13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics, MACS 2019
Country/Territory	Pakistan
City	Karachi
Period	14/12/19 → 15/12/19

Keywords

correlation analysis
data driven
image processing
two-dimensional

Access to Document

10.1109/MACS48846.2019.9024798

Cite this

Khokhar, M. S., Cheng, K., Ayoub, M., Zakria, & Rub, N. E. (2019). Data Driven Processing Via Two-Dimensional Spearman Correlation Analysis (2D-SCA). In 2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS) (pp. 1-7). Article 9024798 (MACS 2019 - 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MACS48846.2019.9024798

Khokhar, Muhammad Saddam ; Cheng, Keyang ; Ayoub, Misbah et al. / Data Driven Processing Via Two-Dimensional Spearman Correlation Analysis (2D-SCA). 2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS). Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1-7 (MACS 2019 - 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics, Proceedings).

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title = "Data Driven Processing Via Two-Dimensional Spearman Correlation Analysis (2D-SCA)",

abstract = "This paper introduces an algorithm two-dimensional Spearman correlation analysis; the present algorithm is the extension of classical Spearman correlation analysis through algebraic solution for multivariate two-dimensional monotonic (linear or non-linear) multi-media datasets. In a way, two different images with nonlinearity challenges like different dimensions are processed with correspondence techniques such as reshaping images into 1D or vectors. Further, it can reduce dimension reduction along with quadratic algorithm complexity. Due to segmentation of matrices and tied rank ability of spearman correlation analysis. The implementation of proposed algorithm performs on four remarkable dataset. The results demonstration is helpful for researchers to choose finger image impression dataset with algorithm performance and sensors related techniques.",

keywords = "correlation analysis, data driven, image processing, two-dimensional",

author = "Khokhar, \{Muhammad Saddam\} and Keyang Cheng and Misbah Ayoub and Zakria and Rub, \{Nida E.\}",

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language = "English",

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Khokhar, MS, Cheng, K, Ayoub, M, Zakria & Rub, NE 2019, Data Driven Processing Via Two-Dimensional Spearman Correlation Analysis (2D-SCA). in 2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)., 9024798, MACS 2019 - 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics, Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1-7, 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics, MACS 2019, Karachi, Pakistan, 14/12/19. https://doi.org/10.1109/MACS48846.2019.9024798

Data Driven Processing Via Two-Dimensional Spearman Correlation Analysis (2D-SCA). / Khokhar, Muhammad Saddam; Cheng, Keyang; Ayoub, Misbah et al.
2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS). Institute of Electrical and Electronics Engineers Inc., 2019. p. 1-7 9024798 (MACS 2019 - 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics, Proceedings).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

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AU - Rub, Nida E.

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AB - This paper introduces an algorithm two-dimensional Spearman correlation analysis; the present algorithm is the extension of classical Spearman correlation analysis through algebraic solution for multivariate two-dimensional monotonic (linear or non-linear) multi-media datasets. In a way, two different images with nonlinearity challenges like different dimensions are processed with correspondence techniques such as reshaping images into 1D or vectors. Further, it can reduce dimension reduction along with quadratic algorithm complexity. Due to segmentation of matrices and tied rank ability of spearman correlation analysis. The implementation of proposed algorithm performs on four remarkable dataset. The results demonstration is helpful for researchers to choose finger image impression dataset with algorithm performance and sensors related techniques.

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KW - data driven

KW - image processing

KW - two-dimensional

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Khokhar MS, Cheng K, Ayoub M, Zakria, Rub NE. Data Driven Processing Via Two-Dimensional Spearman Correlation Analysis (2D-SCA). In 2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS). Institute of Electrical and Electronics Engineers Inc. 2019. p. 1-7. 9024798. (MACS 2019 - 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics, Proceedings). doi: 10.1109/MACS48846.2019.9024798

Data Driven Processing Via Two-Dimensional Spearman Correlation Analysis (2D-SCA)

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