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Proceedings Paper

Determination of dry matter content in composted material based on digital images of compost taken under mixed visible and UV-A light
Author(s): M. Zaborowicz; D. Wojcieszak; K. Górna; S. Kujawa; R. J. Kozłowski; K. Przybył; N. Mioduszewska; P. Idziaszek; P. Boniecki
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Paper Abstract

The aim of the research was to investigate the possibility of using the methods of neural image analysis and neural modeling to determine the content of dry weight of compost based on photographs taken under mixed visible and UV-A light conditions. The research lead to the conclusion that the neural image analysis may be a useful tool in determining the quantity of dry matter in the compost. Generated neural model RBF 30:30-8-1:1 characterized by RMS error 0,076378 and this networks is more effective than RBF 19:19-2:1:1 which works in visible light conditions.

Paper Details

Date Published: 29 August 2016
PDF: 5 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100332G (29 August 2016); doi: 10.1117/12.2243985
Show Author Affiliations
M. Zaborowicz, Poznan Univ. of Life Sciences (Poland)
D. Wojcieszak, Poznan Univ. of Life Sciences (Poland)
K. Górna, Poznan Univ. of Life Sciences (Poland)
S. Kujawa, Poznan Univ. of Life Sciences (Poland)
R. J. Kozłowski, Poznan Univ. of Life Sciences (Poland)
K. Przybył, Poznan Univ. of Life Sciences (Poland)
N. Mioduszewska, Poznan Univ. of Life Sciences (Poland)
P. Idziaszek, Poznan Univ. of Life Sciences (Poland)
P. Boniecki, Poznan Univ. of Life Sciences (Poland)


Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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