| dc.contributor.author | Buluş, E. | |
| dc.date.accessioned | 2022-05-11T14:15:58Z | |
| dc.date.available | 2022-05-11T14:15:58Z | |
| dc.date.issued | 2021 | |
| dc.identifier.isbn | 9781665429085 | |
| dc.identifier.uri | https://doi.org/10.1109/UBMK52708.2021.9558915 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.11776/6135 | |
| dc.description | 6th International Conference on Computer Science and Engineering, UBMK 2021 -- 15 September 2021 through 17 September 2021 -- 176826 | en_US |
| dc.description.abstract | Today, it is desired to make various inferences from images quickly with artificial intelligence methods. One of the most important reasons for this is the increase in social media environments. On the other hand, it is desired to evaluate the images with artificial intelligence methods for security purposes. In this study, it was investigated how much the determination of the gender of a person from a face photograph can be done with existing methods. For this purpose, two of the widely used Convolutional Neural Network (CNN) methods were selected. The selected methods are caffemodel and vgg16 model. The accuracy of both methods was tested for the prepared male and female face images. © 2021 IEEE | en_US |
| dc.language.iso | tur | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
| dc.identifier.doi | 10.1109/UBMK52708.2021.9558915 | |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | CaffeModel | en_US |
| dc.subject | Convolutional Neural Network (CNN) | en_US |
| dc.subject | Gender recognition | en_US |
| dc.subject | Opencv | en_US |
| dc.subject | VGG16 model | en_US |
| dc.subject | Convolution | en_US |
| dc.subject | Artificial intelligence methods | en_US |
| dc.subject | Caffemodel | en_US |
| dc.subject | Convolutional neural network | en_US |
| dc.subject | Gender recognition | en_US |
| dc.subject | Neural network method | en_US |
| dc.subject | Neural network model | en_US |
| dc.subject | Opencv | en_US |
| dc.subject | Social media | en_US |
| dc.subject | VGG16 model | en_US |
| dc.subject | Convolutional neural networks | en_US |
| dc.title | Gender Determination from Pictures with CNN Models | en_US |
| dc.title.alternative | CNN Modelleri ile Resimlerden Cinsiyet Tayini | en_US |
| dc.type | conferenceObject | en_US |
| dc.relation.ispartof | Proceedings - 6th International Conference on Computer Science and Engineering, UBMK 2021 | en_US |
| dc.department | Fakülteler, Çorlu Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | en_US |
| dc.identifier.startpage | 310 | en_US |
| dc.identifier.endpage | 313 | en_US |
| dc.institutionauthor | Buluş, E. | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.authorscopusid | 8240135200 | |
| dc.identifier.scopus | 2-s2.0-85125866364 | en_US |
