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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM65028

Music-Gen-Classification Using Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM65028

Volume:

10 |

6 |

Jun 2026

Pages:

1-2

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
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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Authors

CNB

CHETHAN N B

COMPUTER SCIENCE

U B D T C E

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IH

IRSHAD HUSSAIN

COMPUTER SCIENCE

U B D T C E

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DIB

Dr.Mohammad Irshad B

COMPUTER SCIENCE

U B D T C E

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Full ArticlesAcceptance Certificate

Abstract

Plant identification plays a crucial role in agriculture, environmental monitoring, and botanical research. Traditional methods rely on flowers which are seasonal. This paper presents a machine learning approach using leaf images. The system applies preprocessing, feature extraction, and classification techniques to identify plant species accurately.

KEYWORDS

Machine Learning Leaf Classification Image Processing Plant Identification

Cite This Article

CHETHAN N B, IRSHAD HUSSAIN, Dr.Mohammad Irshad B, "Music-Gen-Classification Using Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-2, Jun 2026.

Full Article/Conclusion

This paper presents a machine learning-based system for classifying flowering plants using leaf images. The approach eliminates dependency on flowers and provides an efficient and scalable solution for plant identification. The results demonstrate the effectiveness of leaf-based classification in real-world applications.

References

[1]   J. Smith, “Plant Classification Using Machine Learning,” Journal of AI Research, 2020. [2]   A. Kumar, “Leaf Recognition Techniques,” IEEE Conference, 2021. [3]   Online datasets and image repositories.

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Publication Date

6/19/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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0

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3

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5

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This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.

Conflict of Interest

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

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No funding information available for this research.

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