Modern Learnıng Technıques And Plant Image Classıfıcatıon
| dc.contributor.author | Ünal, Metehan | |
| dc.contributor.author | Bostancı, Erhan | |
| dc.contributor.author | Güzel, Mehmet Serdar | |
| dc.contributor.author | Aydın, Ayhan | |
| dc.contributor.department | Bilgisayar Mühendisliği | tr_TR |
| dc.contributor.faculty | Mühendislik Fakültesi | tr_TR |
| dc.date.accessioned | 2021-12-01T12:03:41Z | |
| dc.date.available | 2021-12-01T12:03:41Z | |
| dc.date.issued | 2020-07-01 | |
| dc.description.abstract | The intelligent machines concept is born in sci-fi scenarios. Today it seems to be we are much closer to realizing this idea than ever before. By imitating the human nervous system, machines can learn many things. This paper explains modern learning techniques like artificial neural networks, transfer learning. Later purposes an experiment to classify plant seedling images to test the transfer learning with two different CNN architectures. Although the architects were not actually created for this task, result were quite accurate for a different classification task. | tr_TR |
| dc.description.index | Trdizin | tr_TR |
| dc.identifier.endpage | 163 | tr_TR |
| dc.identifier.issn/e-issn | 2618-6462 | |
| dc.identifier.issue | 2 | tr_TR |
| dc.identifier.startpage | 153 | tr_TR |
| dc.identifier.uri | http://hdl.handle.net/20.500.12575/76563 | |
| dc.identifier.volume | 62 | tr_TR |
| dc.language.iso | en | tr_TR |
| dc.publisher | Ankara Üniversitesi Fen Fakültesi | tr_TR |
| dc.relation.journal | Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering | tr_TR |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | tr_TR |
| dc.subject | Plan Classification | tr_TR |
| dc.subject | Convolutional Neural Network | tr_TR |
| dc.subject | AlexNet | tr_TR |
| dc.title | Modern Learnıng Technıques And Plant Image Classıfıcatıon | tr_TR |
| dc.type | Article | tr_TR |