Publications

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Author Title Type [ Year(Desc)]
Filters: Author is Juan Ignacio Arribas  [Clear All Filters]
2020
Pourdarbani, R., S. Sabzi, D. Kalantari, R. Karimzadeh, E. Ilbeygi, and J. I. Arribas, "Automatic non-destructive video estimation of maturation levels in Fuji apple (Malus Malus pumila) fruit in orchard based on colour (Vis) and spectral (NIR) data", Biosystems Engineering, vol. 195, pp. 136–151, 2020.
Pourdarbani, R., S. Sabzi, D. Kalantari, J. Luis Hernández-Hernández, and J. I. Arribas, "A Computer Vision System Based on Majority-Voting Ensemble Neural Network for the Automatic Classification of Three Chickpea Varieties", Foods, vol. 9, pp. 113, 2020.
Sabzi, S., R. Pourdarbani, and J. I. Arribas, "A Computer Vision System for the Automatic Classification of Five Varieties of Tree Leaf Images", Computers, vol. 9, pp. 6, 2020.
Abbaspour-Gilandeh, Y., S. Sabzi, F. Azadshahraki, R. Karimzadeh, E. Ilbeygi, and J. I. Arribas, "Non-destructive Estimation of Chlorophyll a Content in Red Delicious Apple Cultivar Based on Spectral and Color Data", Journal of Agricultural Sciences, vol. 26, pp. 339–348, 2020.
Pourdarbani, R., S. Sabzi, D. Kalantari, and J. I. Arribas, "Non-destructive visible and short-wave near-infrared spectroscopic data estimation of various physicochemical properties of Fuji apple (Malus pumila) fruits at different maturation stages", Chemometrics and Intelligent Laboratory Systems, pp. 104147, 2020.
Dadashzadeh, M., Y. Abbaspour-Gilandeh, T. Mesri-Gundoshmian, S. Sabzi, J. Luis Hernández-Hernández, M. Hernández-Hernández, and J. I. Arribas, "Weed Classification for Site-Specific Weed Management Using an Automated Stereo Computer-Vision Machine-Learning System in Rice Fields", Plants, vol. 9, pp. 559, 2020.
Sabzi, S., Y. Abbaspour-Gilandeh, and J. I. Arribas, "An automatic visible-range video weed detection, segmentation and classification prototype in potato field", Heliyon, vol. 6, pp. e03685, 2020.
Sabzi, S., H. Javadikia, and J. I. Arribas, "A three-variety automatic and non-intrusive computer vision system for the estimation of orange fruit pH value", Measurement, vol. 152, pp. 107298, 2020.

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