Pattern of Cow Nose and its Unique Identification through AI

In the field of animal husbandry, livestock identification is a critical aspect of management, health monitoring, and traceability. Traditional methods of cow identification, such as ear tags or physical marks, are prone to errors and limitations, including loss, damage, or illegibility. Recent advances in artificial intelligence (AI) have offered novel solutions to these problems. This research explores the potential of using cow nose patterns for unique identification through AI. The unique physical features of a cow’s nose, such as its pigmentation and patterning, provide a biometric characteristic that can be harnessed for identification. This paper investigates the feasibility, challenges, and methodology of employing AI, particularly deep learning and computer vision, to accurately identify cows based on their nose patterns. The findings highlight the potential benefits of using AI for animal identification, including enhanced accuracy, cost-efficiency, and reliability.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-30
DOI
https://doi.org/10.5281/zenodo.15542721
Primary Topic
Food Supply Chain Traceability
Type
article
Field-Weighted Citation Impact
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article

Pattern of Cow Nose and its Unique Identification through AI

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

Pattern of Cow Nose and its Unique Identification through AI

article en

Abstract

In the field of animal husbandry, livestock identification is a critical aspect of management, health monitoring, and traceability. Traditional methods of cow identification, such as ear tags or physical marks, are prone to errors and limitations, including loss, damage, or illegibility. Recent advances in artificial intelligence (AI) have offered novel solutions to these problems. This research explores the potential of using cow nose patterns for unique identification through AI. The unique physical features of a cow’s nose, such as its pigmentation and patterning, provide a biometric characteristic that can be harnessed for identification. This paper investigates the feasibility, challenges, and methodology of employing AI, particularly deep learning and computer vision, to accurately identify cows based on their nose patterns. The findings highlight the potential benefits of using AI for animal identification, including enhanced accuracy, cost-efficiency, and reliability.

Zenodo (CERN European Organization for Nuclear Research)
Ashoka University (IN)
Zero hunger
Openalex Percentile: Top 53%
Food Supply Chain Traceability
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