Applications and Comparisons of Optimization Algorithms Used in Convolutional Neural Networks
dc.authorid | Karci, Ali/0000-0002-8489-8617 | |
dc.authorid | uckan, Taner/0000-0001-5385-6775 | |
dc.authorid | Seyyarer, Ebubekir/0000-0002-8981-0266 | |
dc.authorwosid | Karci, Ali/AAG-5337-2019 | |
dc.authorwosid | uckan, Taner/IZP-9705-2023 | |
dc.contributor.author | Seyyarer, Ebubekir | |
dc.contributor.author | Uckan, Taner | |
dc.contributor.author | Hark, Cengiz | |
dc.contributor.author | Ayata, Faruk | |
dc.contributor.author | Inan, Mevlut | |
dc.contributor.author | Karci, Ali | |
dc.date.accessioned | 2024-08-04T20:56:30Z | |
dc.date.available | 2024-08-04T20:56:30Z | |
dc.date.issued | 2019 | |
dc.department | İnönü Üniversitesi | en_US |
dc.description | International Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 21-22, 2019 -- Inonu Univ, Malatya, TURKEY | en_US |
dc.description.abstract | 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. | en_US |
dc.description.sponsorship | IEEE Turkey Sect,Anatolian Sci,Inonu Univ, Comp Sci Dept,Inonu Univ, Muhendisli Fakultesi | en_US |
dc.identifier.doi | 10.1109/idap.2019.8875929 | |
dc.identifier.uri | https://doi.org/10.1109/idap.2019.8875929 | |
dc.identifier.uri | https://hdl.handle.net/11616/102386 | |
dc.identifier.wos | WOS:000591781100058 | en_US |
dc.identifier.wosquality | N/A | en_US |
dc.indekslendigikaynak | Web of Science | en_US |
dc.language.iso | tr | en_US |
dc.publisher | Ieee | en_US |
dc.relation.ispartof | 2019 International Conference on Artificial Intelligence and Data Processing (Idap 2019) | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Deep learning | en_US |
dc.subject | Convolutional neural networks | en_US |
dc.subject | Optimization algorithms | en_US |
dc.subject | Caltech 101 | en_US |
dc.subject | Cifar-100 | en_US |
dc.title | Applications and Comparisons of Optimization Algorithms Used in Convolutional Neural Networks | en_US |
dc.type | Conference Object | en_US |