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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM49687

Image mining using ML

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM49687

Volume:

9 |

6 |

Jun 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Hitesh giri

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Abstract

The current generation of research scholars is highly motivated to conduct data mining-related studies worldwide. In particular, Mining Image data is one of the most important components of the current situation since it is required for every part of the system, including the Web for publication, hospitals for surgery, businesses for marketing, and engineering for construction. A more objective method of retrieval based on similarity defined in terms of retrieved features is provided by Content-Based Image Retrieval (CBIR), the second component of the image mining system. Using only the query image’s features is a disadvantage of CBIR. Thus, image retrieval based on optimum clusters is a novel technique developed for Utilizing similar information to its fullest potential will improve user interaction with picture retrieval systems. The process of creating the index involves using compact feature vectors, which reflect typical color distributions, to describe the photos based on their color properties.

KEYWORDS

Machine Learning pre-processing Image Mining detection

Cite This Article

Hitesh giri, "Image mining using ML," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 6, Jun 2025.

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Publication Date

6/8/2025

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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