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Application of neural modelling methods in the evaluation of the quality of pork half-carcasses
Author(s): M. Zaborowicz; D. Lisiak; K. Koszela; P. Boniecki; S. Kujawa; W. Mueller; Ł. Gierz; K. Przybył; P. Ślósarz
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Paper Abstract

The paper concerns the implementation of research task no. 4 of the PBS3/B8/26/2015 project, the aim of which was to create models of artificial neural networks determining the meat of pork half-carcasses. As a result, thanks to threedimensional scans of the examined half-carcasses, the characteristic cross-section of half-carcasses was determined and the parameters necessary to determine the meatiness were defined. The neon model realizing this task was RBF 9:9-25- 1:1 network, which for the cross-section of 89 was characterized by test quality 0,9887 and RMSE error 0,1556. The work carried out allowed for the development of an algorithm approved by the European Commission on 11 February 2019 np. 2019/252 and the production of devices ESTIMEAT and MEAT3D

Paper Details

Date Published: 14 August 2019
PDF: 5 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 1117940 (14 August 2019); doi: 10.1117/12.2539781
Show Author Affiliations
M. Zaborowicz, Poznan Univ. of Life Sciences (Poland)
D. Lisiak, Institute of Agricultural and Food Biotechnology (Poland)
K. Koszela, Poznan Univ. of Life Sciences (Poland)
P. Boniecki, Poznan Univ. of Life Sciences (Poland)
S. Kujawa, Poznan Univ. of Life Sciences (Poland)
W. Mueller, Poznan Univ. of Life Sciences (Poland)
Ł. Gierz, Poznan Univ. of Technology (Poland)
K. Przybył, Poznan Univ. of Life Sciences (Poland)
P. Ślósarz, Poznan Univ. of Life Sciences (Poland)


Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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