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14 August 2019 Health properties and evaluation of quality of dried strawberry fruit produced using the convective drying method with neural image analysis
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Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111790C (2019) https://doi.org/10.1117/12.2539784
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China
Abstract
Research was conducted for the purpose of qualitative identification of convection-dried strawberries using artificial neural networks. 2 samples of raw material were subjected to a drying process, each representing different qualitative classes: ripe and overripe fruit. The generated MLP neural network was based on shape and color characteristics; 11 parameters of the quality of dried strawberry were specified. Empirical data was obtained from digital images which served as learning sets for the artificial neural networks simulator. The created neural network was to identify individual learning cases as one of the following cases: "good" - ripe or "bad" - overripe strawberry. Furthermore, a correlation analysis was performed, which showed a strong relationship between some variables.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
K. Przybył, A. Pilarska, A. Duda, D. Wojcieszak, J. Frankowski, K. Koszela, P. Boniecki, S. Kujawa, W. Mueller, Ł. Gierz, and Maciej Zaborowicz "Health properties and evaluation of quality of dried strawberry fruit produced using the convective drying method with neural image analysis", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111790C (14 August 2019); https://doi.org/10.1117/12.2539784
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