29 August 2016 Determination of dry matter content in composted material based on digital images of compost taken under mixed visible and UV-A light
Author Affiliations +
Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100332G (2016) https://doi.org/10.1117/12.2243985
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China
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.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Zaborowicz, M. Zaborowicz, D. Wojcieszak, D. Wojcieszak, K. Górna, K. Górna, S. Kujawa, S. Kujawa, R. J. Kozłowski, R. J. Kozłowski, K. Przybył, K. Przybył, N. Mioduszewska, N. Mioduszewska, P. Idziaszek, P. Idziaszek, P. Boniecki, P. Boniecki, } "Determination of dry matter content in composted material based on digital images of compost taken under mixed visible and UV-A light", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100332G (29 August 2016); doi: 10.1117/12.2243985; https://doi.org/10.1117/12.2243985
PROCEEDINGS
5 PAGES


SHARE
Back to Top