Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Enis Simsar"'
Autor:
Atıf Emre Yüksel, Sadullah Gültekin, Enis Simsar, Şerife Damla Özdemir, Mustafa Gündoğar, Salih Barkın Tokgöz, İbrahim Ethem Hamamcı
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Abstract In this paper, a new powerful deep learning framework, named as DENTECT, is developed in order to instantly detect five different dental treatment approaches and simultaneously number the dentition based on the FDI notation on panoramic X-ra
Externí odkaz:
https://doaj.org/article/395b919faa6d416da49fa4a137d6ff9f
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac5b8e56ee294bf7c6939e2c90bea59e
https://doi.org/10.1109/cvprw56347.2022.00255
https://doi.org/10.1109/cvprw56347.2022.00255
The discovery of interpretable directions in the latent spaces of pre-trained GAN models has recently become a popular topic. In particular, StyleGAN2 has enabled various image generation and manipulation tasks due to its rich and disentangled latent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::349ea5f63d8c3d4c793693039585bcbc
With the advent of deep learning, estimating depth from a single RGB image has recently received a lot of attention, being capable of empowering many different applications ranging from path planning for robotics to computational cinematography. Neve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf46121d5edd6c245ad350ef0f243da0
http://arxiv.org/abs/2112.01521
http://arxiv.org/abs/2112.01521
In this paper, we propose a graph-based image-to-image translation framework for generating images. We use rich data collected from the popular creativity platform Artbreeder (http://artbreeder.com), where users interpolate multiple GAN-generated ima
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f411597b771ce85770b06dee19253e0b
https://aperta.ulakbim.gov.tr/record/237762
https://aperta.ulakbim.gov.tr/record/237762
Publikováno v:
SIU
In this study, we compare deep learning methods for generating images of handwritten characters. This problem can be thought of as a restricted Turing test: A human draws a character from any desired alphabet and the system synthesizes images with si
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6becc4acf579f62c6e6feeea9df8e51a
https://doi.org/10.1109/siu.2019.8806416
https://doi.org/10.1109/siu.2019.8806416