Crossref DOIMemberCiteFactoropen accessissn
SJIF Impact Factor 8.659 | ISSN: 2582-3930
IJSREM Logo

International Journal of Scientific Research in Engineering and Management

(Gateway to Global Scholars - An International, Scholarly, Multi-Disciplinary, Open Access Journal)

Peer-Reviewed Journal Designed to Meet UGC's Quality Parameters

HomeCurrent IssuePast IssuesPay OnlineConferencesEditorial BoardAbout UsContact Us
IJSREM

Loading article...

Follow Us

  • Google Scholar
  • ResearchGate
  • Academia.edu
  • Mendeley
  • LinkedIn
  • Facebook
  • Instagram

Journal Policies

  • Peer Review Policy
  • Publication Ethics
  • Copyright Infringement
  • Refund & Cancellation Policy
  • Terms and Conditions
  • Privacy Policy

Journal Identifiers & Licenses

  • ISSN Verified: 2582-3930ISSN Verified: 2582-3930
  • Crossref DOI: 10.55041Crossref DOI: 10.55041
  • SJIF Ranking: 08.659SJIF Ranking: 08.659
  • Licensed under CC BY 4.0Licensed under CC BY 4.0
  • ISO Certification: 9001:2015ISO Certification: 9001:2015
  • Indexed & Cited In: Google ScholarIndexed & Cited In: Google Scholar

Contact Us

International Journal of Scientific Research in Engineering and Management (IJSREM)

#62/1, New No 7, 1st Cross, 2nd Main, Ganganagar, R T Nagar, Bangalore North, Bangalore, Karnataka, India – 560032
[email protected]+91 93911 67991
logos
logos
Working Hours

Mon – Sat: 9:00 AM – 6:00 PM

Sunday: 10:00 AM – 4:00 PM

+91 93911 67991

© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

DisclaimerPrivacy PolicyTerms and Conditions
ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM18839

Animal Species Identification using Deep Learning

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM18839

Volume:

7 |

4 |

Apr 2023

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.

Share this article:

Authors

AP

Aashish Pagare

AS

Aditya Sharma

AV

Aman Verma

AKY

Amit Kumar Yadav

Author Services & Downloads

Full Articles

Abstract

Bird identification is a difficult undertaking that frequently results in ambiguous labeling. Even skilled bird watchers dispute the species of a bird when presented with an image of one. It’s a demanding task that tests both people and computers’ visual talents. For example, for different scenarios, animals come with different sizes, forms, colors and from a human viewpoint with different angles. Indeed, the images show different differences that need to be recorded as image recognition of bird & snake species. It is also easier for people to identify animals in the pictures. Identification of animal species is a challenging task often resulting in ambiguous labels. Even professional Wildlife watchers sometimes disagree on the species given an image of animals.

KEYWORDS

Cite This Article

Aashish Pagare, Aditya Sharma, Aman Verma, Amit Kumar Yadav, "Animal Species Identification using Deep Learning," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 4, Apr 2023. https://doi.org/10.55041/IJSREM18839

Full Article/Conclusion

References

Editorial & Review Transparency

Publication Date

10/3/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

Documents

Review Report (Confidential)
Copyright Form (Office)

Article Metrics & Impact

Article Views

0

Total views since publication

PDF Downloads

18

Total downloads since publication

Geographic Reach

5

Indexing, Archiving & Preservation

Google Scholar
Academia
ResearchGate
Crossref
SSRN
Semantic Scholar
Thomson Reuters
WorldCat
Mendeley
OpenAlex
EBSCO
Zenodo

Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.

Ethics, Compliance & Transparency

Plagiarism Screening

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.

Funding Information

No funding information available for this research.

Similar & Recommended Articles

Similar Articles by Topic

Related research in the same subject area

Loading similar articles...