Livestock Vision Studio: An End-to-End Deep Learning Framework for Cattle and Buffalo Breed Recognition

India maintains one of the world's largest populations of cattle and buffaloes, with over 50 recognized indigenous breeds adapted across diverse agro-climatic zones. Accurate breed identification remains central to dairy productivity, genetic conservation, insurance administration, and government traceability initiatives. However, conventional breed recognition relies on subjective expert judgment, which is inconsistent—especially for crossbreds or visually similar breeds.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-02
DOI
https://doi.org/10.5281/zenodo.19980766
Primary Topic
Food Supply Chain Traceability
Type
article
Field-Weighted Citation Impact
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article

Livestock Vision Studio: An End-to-End Deep Learning Framework for Cattle and Buffalo Breed Recognition

Anita Pal, Mohd Afjan, Mohd Altaf, Mohd Anas
Zenodo (CERN European Organization for Nuclear Research)
Food Supply Chain Traceability
article

Livestock Vision Studio: An End-to-End Deep Learning Framework for Cattle and Buffalo Breed Recognition

Anita Pal, Mohd Afjan, Mohd Altaf, Mohd Anas
article en

Abstract

India maintains one of the world's largest populations of cattle and buffaloes, with over 50 recognized indigenous breeds adapted across diverse agro-climatic zones. Accurate breed identification remains central to dairy productivity, genetic conservation, insurance administration, and government traceability initiatives. However, conventional breed recognition relies on subjective expert judgment, which is inconsistent—especially for crossbreds or visually similar breeds.

Zenodo (CERN European Organization for Nuclear Research)
Dr. A.P.J. Abdul Kalam Technical University (IN)
Openalex Percentile: Top 8%
Food Supply Chain Traceability
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