Evidence map›Paper›PMID 38731328›Full record

ArticleAnimals : an open access journal from MDPI2024

Analysis and Comparison of New-Born Calf Standing and Lying Time Based on Deep Learning.

Wenju Zhang, Yaowu Wang, Leifeng Guo, Greg Falzon, Paul Kwan, Zhongming Jin, Yongfeng Li, Wensheng Wang

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

8 authors.

Wenju ZhangAgricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100086, China.ORCID 0000-0002-1396-2757
Yaowu WangAgricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100086, China.ORCID 0000-0001-8853-8988
Leifeng GuoAgricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100086, China.ORCID 0000-0002-2447-2905
Greg FalzonCollege of Science and Engineering, Flinders University, Adelaide, SA 5042, Australia.ORCID 0000-0002-1989-9357
Paul KwanSchool of Engineering and Technology, College of ICT, Central Queensland University, Rockhampton, QLD 4701, Australia.
Zhongming JinAgricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100086, China.ORCID 0000-0002-0920-8292
Yongfeng LiAgricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100086, China.
Wensheng WangAgricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100086, China.

Funding

the Key Research and Development Program of Ningxia Autonomous Region 2022BBF02021the Major Science and Technology Program of Inner Mongolia Autonomous Region 2020ZD0004the National Key Research and Development Program of China 2021YFD1300500the Science and Technology Innovation Project of the Chinese Academy of Agricultural Sciences CAAS-ASTIP-2016-AII
6 · The paper itself

Abstract

Standing and lying are the fundamental behaviours of quadrupedal animals, and the ratio of their durations is a significant indicator of calf health. In this study, we proposed a computer vision method for non-invasively monitoring of calves' behaviours. Cameras were deployed at four viewpoints to monitor six calves on six consecutive days. YOLOv8n was trained to detect standing and lying calves. Daily behavioural budget was then summarised and analysed based on automatic inference on untrained data. The results show a mean average precision of 0.995 and an average inference speed of 333 frames per second. The maximum error in the estimated daily standing and lying time for a total of 8 calf-days is less than 14 min. Calves with diarrhoea had about 2 h more daily lying time (

Indexed as

animal welfarebehaviour monitoringdeep learninghealth indicator

Identifiers

PMID38731328
PMCPMC11083583

What OpenQuestion holds

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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.