Recognition of Foal Nursing Behavior Based on an Improved RT-DETR Model.

Yanhong Liu, Fang Zhou, Wenxin Zheng, Tao Bai, Xinwen Chen, Leifeng Guo

Abstract read

In one paragraph

Article 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. Not yet cited in PubMed.

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6 authors.

Yanhong LiuCollege of Computer and Information Engineering, Xinjiang Agricultural University, Urumqi 830052, China.

Fang ZhouCollege of Information Science and Technology, Shihezi University, Shihezi 832000, China.

Wenxin ZhengCollege of Computer and Information Engineering, Xinjiang Agricultural University, Urumqi 830052, China.

Tao BaiCollege of Computer and Information Engineering, Xinjiang Agricultural University, Urumqi 830052, China.

Xinwen ChenInstitute of Animal Husbandry Quality Standards, Xinjiang Academy of Animal Science, Urumqi 830011, China.

Leifeng GuoCollege of Computer and Information Engineering, Xinjiang Agricultural University, Urumqi 830052, China.ORCID 0000-0002-2447-2905

Funding

the Key R&D Program of Xinjiang Uygur Autonomous Region 2022B02027, 2023B02013

6 · The paper itself

Abstract

Foal nursing behavior is a crucial indicator of healthy growth. The mare being in a standing posture and the foal being in a suckling posture are important markers for foal suckling behavior. To enable the recognition of a mare's standing posture and its foal's suckling posture in stalls, this paper proposes an RT-DETR-Foalnursing model based on RT-DETR. The model employs SACGNet as the backbone to enhance the efficiency of image feature extraction. Furthermore, by incorporating a multiscale multihead attention module and a channel attention module into the Adaptive Instance Feature Integration (AIFI), the model strengthens feature utilization and integration capabilities, thereby improving recognition accuracy. Experimental results demonstrate that the improved RT-DETR achieves a best mAP@50 of 98.5%, increasing by 1.8% compared to the RT-DETR. Additionally, this study achieves real-time statistical analysis of the duration of the foal in the suckling posture, which is one of the important indicators for determining whether the foal is suckling. This has significant implications for the healthy growth of foals.

Indexed as

artificial intelligencebehavior recognitionfeedingfoal suckling

Identifiers

PMID39943111

DOI10.3390/ani15030340

PMCPMC11816262

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LicenceCC BY

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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.