ANIMAL TYPE RECOGNITION AND BREED IDENTIFICATION SYSTEM

An AI-based Animal Breed Identification and Recognition System is designed to automatically identify and classify animal breeds using image processing and deep learning techniques. In the current scenario, identifying animal breeds accurately requires expert knowledge and manual observation, which can be time-consuming, error-prone, and not easily accessible to common users. This often leads to incorrect identification, affecting applications in wildlife monitoring, veterinary care, and research.The proposed system overcomes these limitations by integrating artificial intelligence with a mobile and web-based platform that analyzes images of animals and predicts their breed with high accuracy. The system utilizes advanced deep learning models such as MobileNetV2 to extract features from input images and perform efficient classification. Users can upload or capture images through an intuitive interface, and the system provides instant predictions along with relevant information about the identified breed.Additionally, the system can be extended to include features such as breed information, habitat details, and usage in wildlife conservation and education. The application ensures fast response time, ease of use, and accessibility, allowing users to identify animal breeds anytime and anywhere.Thus, the proposed system offers a scalable, cost-effective, and user-friendly solution that enhances the accuracy of animal classification, reduces dependency on experts, and demonstrates the practical application of artificial intelligence in real-world scenarios.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-26
DOI
https://doi.org/10.5281/zenodo.19783260
Primary Topic
Food Supply Chain Traceability
Type
article
Field-Weighted Citation Impact
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article

ANIMAL TYPE RECOGNITION AND BREED IDENTIFICATION SYSTEM

Aswami M A
Zenodo (CERN European Organization for Nuclear Research)
Food Supply Chain Traceability
article

ANIMAL TYPE RECOGNITION AND BREED IDENTIFICATION SYSTEM

Aswami M A
article en

Abstract

An AI-based Animal Breed Identification and Recognition System is designed to automatically identify and classify animal breeds using image processing and deep learning techniques. In the current scenario, identifying animal breeds accurately requires expert knowledge and manual observation, which can be time-consuming, error-prone, and not easily accessible to common users. This often leads to incorrect identification, affecting applications in wildlife monitoring, veterinary care, and research.The proposed system overcomes these limitations by integrating artificial intelligence with a mobile and web-based platform that analyzes images of animals and predicts their breed with high accuracy. The system utilizes advanced deep learning models such as MobileNetV2 to extract features from input images and perform efficient classification. Users can upload or capture images through an intuitive interface, and the system provides instant predictions along with relevant information about the identified breed.Additionally, the system can be extended to include features such as breed information, habitat details, and usage in wildlife conservation and education. The application ensures fast response time, ease of use, and accessibility, allowing users to identify animal breeds anytime and anywhere.Thus, the proposed system offers a scalable, cost-effective, and user-friendly solution that enhances the accuracy of animal classification, reduces dependency on experts, and demonstrates the practical application of artificial intelligence in real-world scenarios.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 6%
Food Supply Chain Traceability
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