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- Title
Biyomedikal Görüntülerde Derin Öğrenme ile Mevcut Yöntemlerin Kıyaslanması.
- Authors
TOĞAÇAR, Mesut; ERGEN, Burhan
- Abstract
Recent developments in image processing have contributed to the advancement of rapidly developing technological systems. In particular, work on image processing in the health field has further increased its popularity. Whether it is medical images or images on the other side, although the success of existing methods is ensured, the deeper learning model is a model that contributes more in terms of time and performance compared to existing methods. Highperformance results can be obtained on multi-layered images with deep learning model while the existing methods are operated on single layer images. The most important feature of deep learning is that it can process the operations on the image in a single pass and discover the parameters that need to be entered manually. Moreover, as technology companies try to deepen their learning and increase their competitive power among themselves, the methods they have built on deep learning in the scientific sense have begun to be preferred over existing methods. It is envisaged that the data sets in the biomedical field, which is one of the limited access areas of the dataset, to be obtained quickly in the recent times will contribute more to the image processing studies in this area together with the deep learning model.
- Publication
Firat University Journal of Engineering Science, 2019, Vol 31, Issue 1, p109
- ISSN
1308-9072
- Publication type
Article