Applications and Comparisons of Optimization Algorithms Used in Convolutional Neural Networks

Nowadays, 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.