Possibilities of neural image analysis implementation in monitoring of microalgae production as a substrate for biogas plant

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 8334, Issue , 2012, Pages

  Cerbin, Slawomir ^a   Nowakowski, Krzysztof ^b   Dach, Jacek ^b   Pilarski, Krzysztof ^b   Boniecki, Piotr ^b   Przybyl, Jacek ^b   Lewicki, Andrzej ^b  

^a ADAM MICKIEWICZ UNIVERSITY   (Poland)

^b POZNA UNIVERSITY OF LIFE SCIENCES   (Poland)

Author keywords

artificial neural networks; biogas production; microalgae; neural image analysis

Indexed keywords

ARTIFICIAL NEURAL NETWORK TOPOLOGY; AUTOMATIC IMAGE ANALYSIS; BIOGAS PLANTS; BIOGAS PRODUCTION; COMPUTER IMAGE ANALYSIS; DEVELOPMENTAL STAGE; KEYPOINTS; MANAGEMENT IS; MICRO-ALGAE; MICROSCOPIC ANALYSIS; NEURAL MODELS; RAPID ESTIMATION;

BIOGAS; CULTIVATION; IMAGE ANALYSIS; MICROORGANISMS; NEURAL NETWORKS; SUBSTRATES;

ALGAE;

EID: 84874690497     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.954164     Document Type: Conference Paper

References (13)

1. Boniecki, P., Dach, J., Nowakowski, K., Jakubek, A., Neural image analysis of maturity stage during composting of sewage sludge. International Conference on Digital Image Processing (ICDIP 2009), 7-9 March 2009, BANGKOK, Thailand, PROCEEDINGS pp. 200-203, DOI: 10. 1109/ICDIP. 2009. 85 (2009).
2. Boniecki, P., Nowakowski, K., Tomczak, R., J., Neural networks type MLP in the process of identification chosen varieties of maize. 3rd International Conference on Digital Image Processing (ICDIP 2011), 15-17 April 2011, CHENGDU, China, Proceedings of SPIE Volume: 8009, Article Number: 800908, DOI: 10. 1117/12. 896184 (2011).
3. Boniecki P., Weres J., Neural Networks as a Tool in the Analysis of Agricultural Engineering Empirical Systems. Journal of Research and Applications in Agricultural Engineering, Vol. 46(3), p. 73-76 (2001).
4. Chisti, Y. , . Biodiesel from microalgae. Biotechnol. Adv. 25, 294-306. (2007).
5. Guillard, R., R., Lorenzen, C., J. , . Yellow-green algae with chlorophyllide C. Journal of Phycology 8: 10-14 (1972).
6. Hindak, F. , . Freshwater algae. Slovenské Pedagogické Nakladatelstwo, Bratislava, 724 p. (in Slovak). (1978)
7. Javornickỳ P. (ed. ), Revise nekterych method pro zjišt'ovǎ nǐkvantity fitoplantonu (Revision of some methods for the phytoplankton quantity estimation), Scientific Paper 2, Faculty of Technology of Fuel and Water, Institute of Chemical Technology, Prague, 570 283-267 (1958).
8. Nowakowski, K., Boniecki, P., Dach, J., The identification of mechanical corn kernels damages basis on neural image analysis. International Conference on Digital Image Processing (ICDIP 2009), 7-9 March 2009, BANGKOK, Thailand, PROCEEDINGS, pp. 412-415, DOI: 10. 1109/ICDIP. 2009. 78 (2009).
9. Nowakowski, K., Boniecki, P., Tomczak, R., J., Identification process of corn and barley kernels damages using neural image analysis. 3rd International Conference on Digital Image Processing (ICDIP 2011), 15-17 April 2011, CHENGDU, China, Proceedings of SPIE Volume: 8009, Article Number: 80090C, DOI: 10. 1117/12. 896664 (2011).
10. Sturmer, B., Schmid, E., Eder, M., W., Impacts of biogas plant performance factors on total substrate costs. Biomass and Bioenergy 35 1552-1560 (2011).
11. Utermöhl, H., Zur Vervollkomnung der quantitativen Phytoplankton-Methodik. Int Ver Theor Angew 9: 1-38 (1958).
12. Wetzel, R., G., Likens, G., E., Limnological analyses (Third edn, ), Springer-Verlag, New York, 1-429 (2000).
13. Zamallo, C., Vulsteke, E., Albrecht, J. N., Verstraete, W., The techno-economic potential of renewable energy through the anaerobic digestion of microalgae. Bioresource Technology, Vol. 102, Issue 2, 1149-1158 (2011).