Akademik Veri Yönetim Sistemi
Future Technologies Conference, FTC 2025, Munich, Almanya, 6 - 07 Kasım 2025, cilt.1677 LNNS, ss.462-474, (Tam Metin Bildiri)
The amazingly developing and advancing technology in every field also shows itself in image/frame processing. Today, computer vision is an important field of study that can be applied to computers with human vision. Generative networks have been used specifically in studies for a specific purpose. After the generated networks were published, they were effectively used to obtain new data for various purposes. Basically, we aimed to remove an unwanted object from the picture or frame. With this aim, thought that, like human vision, the foresight of the structures that will replace the object planned to be removed has been considered. Accordingly, if an object is in front of a structure/s, the object to be removed, this possible data to replace the object must have a similar transitivity with the structure/s behind it. To do this, it is aimed to create new data by using sub-data in object location surrounding the object, with the approach that the appropriate data to replace the object can be filled by learning from the structures around the object. It was made to replace the object (for pixels containing the object) by generating pixels in object dimensions, using generative networks, and useful results were obtained in this study.