Identifying New Species of Dogs Using Machine Learning Model

Smita Thube, Sonam Singh, Poonam Sadafal, Shweta Lilhare, Pooja Mohbansi, Vishal Borate, Yogesh Mali

2025

Abstract

This paper addresses the challenging problem of breed identification in dogs, whose applications will be very important in disease prevention, genetic research, and personal pet care. We here present an advanced system that identifies dog breeds, using the capabilities of particular CNNs such as InceptionV3, VGG16, Xception, and ResNet for efficient feature extraction. This classification is then refined by a Support Vector Machine algorithm to enhance accuracy. The system is trained on the Stanford Dogs Dataset, a rich collection of diverse dog breed images. The dataset enhances the model's ability to extract meaningful features and classify accurately a wide variety of dog breeds. By iteratively training the model, it learns subtle breed-specific patterns in the images and achieves high classification accuracy at 96.3%.This research not only pushes forward the capabilities of breed identification systems but also offers a flexible approach that can be applied to various practical scenarios where precise breed recognition is critical. With accuracy and adaptability, our system is promising for more extensive applications in biology, veterinary science, and personalized pet management, which would be helpful for insights in the care and research of canines.

Paper Citation

in Harvard Style

Thube S., Singh S., Sadafal P., Lilhare S., Mohbansi P., Borate V. and Mali Y. (2025). Identifying New Species of Dogs Using Machine Learning Model. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 195-202. DOI: 10.5220/0013589200004664

in Bibtex Style

@conference{incoft25,
author={Smita Thube and Sonam Singh and Poonam Sadafal and Shweta Lilhare and Pooja Mohbansi and Vishal Borate and Yogesh Mali},
title={Identifying New Species of Dogs Using Machine Learning Model},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={195-202},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013589200004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - Identifying New Species of Dogs Using Machine Learning Model
SN - 978-989-758-763-4
AU - Thube S.
AU - Singh S.
AU - Sadafal P.
AU - Lilhare S.
AU - Mohbansi P.
AU - Borate V.
AU - Mali Y.
PY - 2025
SP - 195
EP - 202
DO - 10.5220/0013589200004664
PB - SciTePress