Real-time estrus detection in cattle using deep learning-based pose estimation

Open Access

Issue		BIO Web Conf. Volume 123, 2024 The 1^st International Seminar on Tropical Bioresources Advancement and Technology (ISOTOBAT 2024)


Article Number		04009
Number of page(s)		10
Section		Innovative Technologies in Bioresource Science and Engineering
DOI		https://doi.org/10.1051/bioconf/202412304009
Published online		30 August 2024

Nurkholis, S. Nusantoro, A. Awaludin, Perbaikan nilai service per conception (S/C) pada sapi potong dengan pemanfaatan aplikasi kalender reproduksi di Kelompok Ternak Sapi Potong Sidomakmur Desa Umbulrejo Kecamatan Umbulsari Kabupaten Jember, in Proceedings of the Seminar Nasional Hasil Penelitian dan Pengabdian Masyarakat 2018, Makasar, November 10-11 (2018), 101-107 [Google Scholar]
S. Jurame, Sritiasni, I. Womsiwor, Kemampuan peternak dalam mendeteksi berahi (estrus) pada sapi bali, mendukung pelaksanaan inseminasi buatan (IB) di Kampung Mantedi Distrik Masni Kabupaten Manokwari Provinsi Papua Barat. Jurnal Triton. 9, 81-88 (2018) [Google Scholar]
T.A. Sulistya, N. Isnaini, T. Susilawati, Penurunan durasi berbaring harian sapi berahi, sebagai peluang untuk dijadikan teknologi otomatisasi peringatan dini sapi berahi. Jurnal Agripet. 21, 92-96 (2021). https://doi.org/10.17969/agripet.v21i1.19804 [CrossRef] [Google Scholar]
A.M.L. Madureira, L.B. Polsky, T.A. Burnett, B.F. Silper, S. Soriano, A.F. Sica, K.G. Pohler, J.L.M. Vasconcelos, R.L.A. Cerri, Intensity of estrus following an estradiolprogesterone-based ovulation synchronization protocol influences fertility outcomes. Journal of Dairy Science. 102, 3598-3608 (2019). https://doi.org/10.3168/jds.2018-15129 [CrossRef] [Google Scholar]
I.P.S. Agustina, D.N.D.I. Laksmi, I.G.B. Trilaksana, I.M.K. Budiasa, Intensitas estrus sapi bali yang mengalami silent heat. Buletin Veteriner Udayana. 13, 113-117 (2018). https://doi.org/10.24843/bulvet.2021.v13.i02.p01 [Google Scholar]
F. Qi, Y. Wang, Z. Tang, Real-time and effective detection of agricultural pest using an improved YOLOv5 network. Journal of Real-Time Image Proceeding. 20, 33 (2023). https://doi.org/10.1007/s11554-023-01264-0 [CrossRef] [Google Scholar]
D.S. Prasvita, A.M. Arymurthy, D. Chahyati. Deep learning model for automatic detection of oil palm trees in Indonesia with YOLO-V5, in Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology (SIET '23). Association for Computing Machinery, New York, NY, USA, 39-44 (2023). https://doi.org/10.1145/3626641.3626924 [CrossRef] [Google Scholar]
Z. Zheng, J. Li, L. Qin, YOLO-BYTE: An efficient multi-object tracking algorithm for automatic monitoring of dairy cows, Computers and Electronics in Agriculture. 209 (2023). https://doi.org/10.1016/i.compag.2023.107857 [CrossRef] [Google Scholar]
C. Agnew, D. Mewada, E.M. Grua, C. Eising, P. Denny, M. Heffernan, K. Tierney, [Google Scholar]
P.V.D. Ven, A. Scanlan, Detecting the overfilled status of domestic and commercial bins using computer vision. Intelligent Systems with Applications. 18, (2023). https://doi.org/10.1016/j.iswa.2023.200229 [Google Scholar]
J. Li, X. Zhao, L. Kong, L. Zhang, Z. Zou, Construction Activity Recognition Method Based on Object Detection, Attention Orientation Estimation, and Person ReIdentification. Buildings. 14(6), 1644 (2024). https://doi.org/10.3390/buildings14061644 [CrossRef] [Google Scholar]
J. Khairunissa, S. Wahjuni, I.R.H. Soesanto, W. Wulandari, Detecting Poultry Movement for Poultry Behavioral Analysis using The Multi-Object Tracking (MOT) Algorithm. 2021 8th International Conference on Computer and Communication Engineering (ICCCE), Kuala Lumpur, Malaysia, 265-268 (2021). https://doi.org/10.1109/ICCCE50029.2021.9467144 [Google Scholar]
S. Aleyda, I. Jaya, M. Iqbal, Object tracking-based deep learning for calculating the quantity of eel seedlings (Anguilla bicolor), BIO Web of Conferences. 106, (2024). https://doi.org/10.1051/bioconf/202410601006 [CrossRef] [EDP Sciences] [Google Scholar]
I. Ayuningtias, I. Jaya, M. Iqbal, Identification of yellowfin tuna (Thunnus albacares), mackerel tuna (Euthynnus affinis), and skipjack tuna (Katsuwonus pelamis) using deep learning, IOP Conf. Series: Earth and Environmental Science. 944, (2021). https://doi.org/10.1088/1755-1315/944/1/012009 [Google Scholar]
T.D. Pereira, D.E. Aldarondo, L. Willmore, M. Kislin, S.S.H. Wang, M Murthy, J.W. Shaevitz, Fast animal pose estimation using deep neural networks. Nat Methods. 16, 117-125 (2019). https://doi.org/10.1038/s41592-018-0234-5 [CrossRef] [PubMed] [Google Scholar]
N.M. Arago, C.I. Alvarez, A.G. Mabale, C.G. Legista, N.E. Repiso, R.R.A. Robles, T.M. Amado, R.L. JordaJr., A.C. Thio-ac, J.S. Velasco, L.K.S. Tolentino, Automated estrus detection for dairy cattle through neural networks and bounding box corner analysis, International Journal of Advanced Computer Science and Applications (IJACSA). 11, (2020). http://dx.doi.org/10.14569/IJACSA.2020.0110935 [Google Scholar]
U. Riaz, M. Idris, M. Ahmed, F. Ali, L. Yang, Infrared thermography as a potential non-invasive tool for estrus detection in cattle and buffaloes, Animals. 13, (2023). https://doi.org/10.3390/ani13081425 [CrossRef] [Google Scholar]
C. Chen, W. Zhu, T. Norton, Behaviour recognition of pigs and cattle: Journey from computer vision to deep learning, Computers and Electronics in Agriculture. 187, (2021). https://doi.org/10.1016/i.compag.2021.106255 [Google Scholar]
R. Dhandapani, S.M.H Al-Ghafri, Implementation of facial mask detection and verification of vaccination certificate using Jetson Xavier kit, IOP Conference Series: Earth and Environmental Science. 1055, (2022). https://doi.org/10.1088/1755-1315/1055/1/012013 [CrossRef] [Google Scholar]

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