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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM13307

Animal Species Detection

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM13307

Volume:

6 |

5 |

May 2022

Pages:

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

RS

Rohan Singh

AS

Anurag Shukla

SS

Swati Singh

TF

Tuba Fatma

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Abstract

Exploring wildlife in their natural habitat is important. This proposed activity develops an algorithm for finding animals in wildlife. With so many different animals, identifying yourself can be a daunting task. This algorithm classifies animals based on their images so that we can monitor them effectively. Detection and classification of animals can help prevent animal car accidents, track animals and prevent theft. This can be achieved by using active deep learning algorithms. Effective and reliable monitoring of wildlife in their natural environment is essential. This project develops an algorithm for finding out the animal species around us. Research based on finding animals is useful in many real-life programs.

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Cite This Article

Rohan Singh, Anurag Shukla, Swati Singh, Tuba Fatma, "Animal Species Detection," International Journal of Scientific Research in Engineering and Management, vol. 6, no. 5, May 2022.

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Publication Date

5/16/2022

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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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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