Machine Learning For Product Quality Inspection - Citak, Erol; Genç, Yakup (IEEE, 2017)
Pistachio is widely consumed as food which requires the nut to be cracked before usage. Automating the cracking process requires quality control which can be done visually. A system developed to perform this task provides over 98% accuracy. First, the pistachio is segmented from the background using support vector regression (SVR) or deep convolutional networks. Then a classification method based on deep neural networks (FistikNet) is employed to decide the quality of the crack. A large data set is collected to train and test the system.
25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY
Keywords: Deep Learning; SVR; Segmentation; Classification