Evidence map›Paper›PMID 40281960›Full record

ReviewAnimals : an open access journal from MDPI2025

A Review of You Only Look Once Algorithms in Animal Phenotyping Applications.

Guangbo Li, Rui Jian, Xie Jun, Guolong Shi

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Animals : an open access journal from MDPI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Guangbo LiCollege of Command and Control Engineering, Army Engineering University of the People's Liberation Army, Nanjing 210007, China.ORCID 0009-0008-4791-3698
Rui JianCollege of Electronic and Information Engineering, Huaibei Institute of Technology, Huaibei 235000, China.
Xie JunCollege of Command and Control Engineering, Army Engineering University of the People's Liberation Army, Nanjing 210007, China.
Guolong ShiSchool of Information and Artificial Intelligence, Anhui Agricultural University, Hefei 230036, China.

Funding

the General Project for Teaching and Research on Quality Engineering in Anhui Province 2023jyxm1009 and 2023xjzlts117 and 2023sdxx145the Major Project for Natural Science Research of the Department of Education of Anhui Province 2024AH040217the Special Project for Standardization of Quality Infrastructure in Anhui Province 2023MKS14the Youth Fund of the National Natural Science Foundation of China 62303018
6 · The paper itself

Abstract

Animal phenotyping recognition is a pivotal component of precision livestock management, holding significant importance for intelligent farming practices and animal welfare assurance. In recent years, with the rapid advancement of deep learning technologies, the YOLO algorithm-as the pioneering single-stage detection framework-has revolutionized the field of object detection through its efficient and rapid approach and has been widely applied across various agricultural domains. This review focuses on animal phenotyping as the research target structured around four key aspects: (1) the evolution of YOLO algorithms, (2) datasets and preprocessing methodologies, (3) application domains of YOLO algorithms, and (4) future directions. This paper aims to offer readers fresh perspectives and insights into animal phenotyping research.

Indexed as

animal phenotypedatasetdeep learningYOLO-series algorithms

Identifiers

PMID40281960
PMCPMC12023960

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.