Seyyarer, EbubekirUckan, TanerHark, CengizAyata, FarukInan, MevlutKarci, Ali2024-08-042024-08-042019https://doi.org/10.1109/idap.2019.8875929https://hdl.handle.net/11616/102386International Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 21-22, 2019 -- Inonu Univ, Malatya, TURKEYNowadays, it is clear that the old mathematical models are incomplete because of the large size of image data set. For this reason, the Deep Learning models introduced in the field of image processing meet this need in the software field In this study, Convolutional Neural Network (CNN) model from the Deep Learning Algorithms and the Optimization Algorithms used in Deep Learning have been applied to international image data sets. Optimization algorithms were applied to both datasets respectively, the results were analyzed and compared The success rate was approximately 96.21% in the Caltech 101 data set, while it was observed to be approximately 10% in the Cifar-100 data set.trinfo:eu-repo/semantics/closedAccessDeep learningConvolutional neural networksOptimization algorithmsCaltech 101Cifar-100Conference Object10.1109/idap.2019.8875929WOS:000591781100058N/A