IEMEK Journal of Embedded Systems and Applications (대한임베디드공학회논문지)

Institute of Embedded Engineering of Korea (대한임베디드공학회)
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Deep Learning-Based Pig Weight Estimation Algorithm Using Mobile Devices

이동형 디바이스를 이용한 딥러닝 기반의 돼지 무게 추정 알고리즘

  • Received : 2021.02.09
  • Accepted : 2021.04.01
  • Published : 2021.04.30
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Abstract

This paper proposes a deep learning algorithm for estimating pig weight. The proposed algorithm estimates the weight of a pig using the point cloud obtained through a mobile device. The proposed model is based on the PointNet which is widely used in the point cloud data. Through the optimization of the PointNet, the proposed method not only improves the accuracy, but also reduces the computational complexity. The accuracy (82.4 %) of the proposed method was about 3 % higher than that of the conventional method (79.4 %). Also, the numbers of the trainable parameters for the PointNet and the proposed method were 3,1 4,7 1 and 150,5 4, respectively. That is, the proposed method used only 5 % of trainable parameters compared to the PointNet. The developed model makes it easier and faster to measure the weight of a pig than the conventional method.

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Acknowledgement

본 연구는 2020년도 정부(과학기술정보통신부)의 재원으로 과학기술일 자리진흥원의 지원을 받아 수행되었습니다. (1711121241) 또한, 본 연구는 과학기술정보통신부에서 지원하는 DGIST 기관고유사업에 의해 수행되었 습니다 (21-IT-10-03)

References

  1. https://www.kostat.go.kr/portal/korea/kor_nw/1/1/index.board?bmode=read&aSeq=386478
  2. C N. Groesbeck, K R. Lawrence, M G. Young, Robert D. Goodband, Joel M. DeRouchey, Michael D. Tokach, Jim L. Nelssen, Steven S. Dritz "Using Heart Girth to Determine Weight in Finishing Pigs," Kansas Agricultural Experiment Station Research Reports, pp. 166-168, 2002.
  3. M. Kashiha, C. Bahr, S. Ott, C. Moons, T. Niewold, F. Odberg, D. Berckmans, "Weight Estimation of Pigs Using Top-view Image Processing," in Proceeding International Conference Image Ananlysis and Recongnition, pp. 496-503, 2014.
  4. M. Kashiha, C. Bahr, S. Ott, C. Moons, T. Niewold, F. Odberg, D. Berckmans, "Automatic Weight Estimation of Individual Pigs Using Image Analysis," Computers and Electronics in Agriculture, Vol. 107, pp. 38-44, 2014. https://doi.org/10.1016/j.compag.2014.06.003
  5. M. Lu. T. Norton, A. Youssef, N. Radojkovic, A. Fernandez, D. Berckmans, "Extracting Boby Surface Dimensions from Top-view Images of Pigs," International Journal of Agricultureal and Biological Engineering, Vol. 11, No. 5, pp. 182-1191, 2018. https://doi.org/10.25165/j.ijabe.20181105.4054
  6. A. Pezzuoloa, M. Guarinob, L. Sartoria, L. Gonzalezc, F. Marinelloa, "On-barn Pig Weight Estimaton Based on Body Measurments by a Kinect v1 Depth Camera," Computers and Electronics in Agriculture, Vol. 148, pp. 29-36, 2018. https://doi.org/10.1016/j.compag.2018.03.003
  7. Y. Cang, H. He, Y. Qiao, "An Intelligent Pig Weights Estimate Method Based on Deep Learning in Sow Stall Environments." IEEE Access, 7, pp. 164867-164875, 2019. https://doi.org/10.1109/access.2019.2953099
  8. C. R. Qi, H. Su, K. Mo, and L. J. Guibas, "Pointnet: Deep Learning on Point sets for 3d Classification and Segmentation," Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 652-680, 2017.