Enhancing cattle production and management through convolutional neural networks. A review

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12220%2F24%3A43908042" target="_blank" >RIV/60076658:12220/24:43908042 - isvavai.cz</a>

Alternative codes found

RIV/60076658:12410/24:43908042

Result on the web

<a href="https://cjas.agriculturejournals.cz/artkey/cjs-202403-0001_enhancing-cattle-production-and-management-through-convolutional-neural-networks-a-review.php" target="_blank" >https://cjas.agriculturejournals.cz/artkey/cjs-202403-0001_enhancing-cattle-production-and-management-through-convolutional-neural-networks-a-review.php</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.17221/124/2023-CJAS" target="_blank" >10.17221/124/2023-CJAS</a>

Result language

angličtina

Original language name

Enhancing cattle production and management through convolutional neural networks. A review

Original language description

The rise in demand for animal products associated with global population growth has driven the world toward precision livestock farming, where convolutional neural networks (CNN) have gained increasing attention due to their potential to enhance animal health, productivity, and welfare. However, the effectiveness and generalizability of CNN applications in cattle production are limited by several challenges and limitations, which require further research and development to address. This systematic literature review aims to provide a comprehensive overview of the applications of CNN in cattle production. It identified some potential applications of CNN in this field and highlighted the challenges and limitations that need to be addressed to improve the effectiveness and efficiency of CNN applications in cattle production. It also provides valuable insights for researchers, practitioners, and policymakers interested in the use of CNN to enhance cattle production practices, animal welfare, and sustainability. Additionally, it also provides the reader with a summary of the literature on the fundamental concepts of convolutional neural networks and their commonly used model architectures in cattle production. This is because agriculture digitalisation is going more multidisciplinary and people from different areas of expertise may find it helpful to learn more from a combined source.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

40201 - Animal and dairy science; (Animal biotechnology to be 4.4)

Project

<a href="/en/project/FW03010447" target="_blank" >FW03010447: Development of an intelligent system for increasing the performance of dairy cattle using artificial intelligence methods</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Czech Journal of Animal Science : Živočišná výroba

ISSN

1212-1819

e-ISSN

1805-9309

Volume of the periodical

69

Issue of the periodical within the volume

3

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

14

Pages from-to

75-88

UT code for WoS article

001192400900001

EID of the result in the Scopus database

2-s2.0-85189366356