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In commercial egg farming industries, the automatic sorting of defective eggs is economically and healthily important. Nowadays, detect of defective eggs is performed manually. This situation involves time consuming, tiring and complex processes. For all these reasons, automatic classification of defects that may occur on the egg surface has become a very important issue. For this purpose, in this study, classification of egg defects was performed using AlexNet, VGG16, VGG19, SqueezeNet,doi:10.24925/turjaf.v9i3.559-567.4046 fatcat:ueq23buxw5bffkwioyth56znru