UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
Call for Paper
Volume 11 | Issue 10 | October 2024

JETIREXPLORE- Search Thousands of research papers



WhatsApp Contact
Click Here

Published in:

Volume 10 Issue 4
April-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

Unique Identifier

Published Paper ID:
JETIR2304A69


Registration ID:
513730

Page Number

k489-k494

Share This Article


Jetir RMS

Title

Animal Identification And Detection Of Species

Abstract

Abstract: Animal identification and species detection play crucial roles in wildlife conservation, ecological research, and biodiversity monitoring. In recent years, convolutional neural networks (CNNs), a type of deep learning algorithm, have shown remarkable success in various computer vision tasks, including animal identification and species detection. This paper comprehensively reviews current state-of-the-art animal identification and species detection techniques using CNN. The paper discusses the challenges associated with animal identification and species detection, including variations in animal appearance, complex backgrounds, and limited availability of labeled training data. In this study, we propose a deep learning solution based on Convolution Neural Networks (CNN) predict whether the animal belongs to which classes and their species. It also uses a pre-trained model and develops a solution to the same problem. We then explore a variety of CNN-based approaches that have been developed to address these challenges, including transfer learning, fine-tuning, and data augmentation techniques. This paper also describes, for example, various CNN architectures and their applications for animal identification and species discovery.

Key Words

Animal detection; species identification; Convolutional neural Network (CNN);

Cite This Article

"Animal Identification And Detection Of Species", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 4, page no.k489-k494, April-2023, Available :http://www.jetir.org/papers/JETIR2304A69.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Animal Identification And Detection Of Species", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 4, page no. ppk489-k494, April-2023, Available at : http://www.jetir.org/papers/JETIR2304A69.pdf

Publication Details

Published Paper ID: JETIR2304A69
Registration ID: 513730
Published In: Volume 10 | Issue 4 | Year April-2023
DOI (Digital Object Identifier):
Page No: k489-k494
Country: Amravati/, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


Preview This Article


Downlaod

Click here for Article Preview

Download PDF

Downloads

000180

Print This Page

Current Call For Paper

Jetir RMS