Zobrazeno 1 - 10
of 126
pro vyhledávání: '"Gozde Bozdagi Akar"'
Autor:
A. Emre Kavur, Naciye Sinem Gezer, Mustafa Barış, Yusuf Şahin, Savaş Özkan, Bora Baydar, Ulaş Yüksel, Çağlar Kılıkçıer, Şahin Olut, Gözde Bozdağı Akar, Gözde Ünal, Oğuz Dicle, M. Alper Selver
Publikováno v:
Diagnostic and Interventional Radiology, Vol 26, Iss 1, Pp 11-21 (2020)
PURPOSE:To compare the accuracy and repeatability of emerging machine learning based (i.e. deep) automatic segmentation algorithms with those of well-established semi-automatic (interactive) methods for determining liver volume in living liver transp
Externí odkaz:
https://doaj.org/article/20139c9b3c984837993694b11ba5322f
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2009 (2008)
We consider an error-resilient stereoscopic streaming system that uses an H.264-based multiview video codec and a rateless Raptor code for recovery from packet losses. One aim of the present work is to suggest a heuristic methodology for modeling the
Externí odkaz:
https://doaj.org/article/c66c98ebd77e4891b00718928975cf6c
Publikováno v:
2023 IEEE International Conference on Consumer Electronics (ICCE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2f608142acb63734e473be591d713be
https://doi.org/10.1109/icce56470.2023.10043501
https://doi.org/10.1109/icce56470.2023.10043501
Autor:
Emre Bulbul, Gozde Bozdagi Akar
Publikováno v:
2022 30th Signal Processing and Communications Applications Conference (SIU).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e7228f0a1687a04c081155feb3b2ba3
https://doi.org/10.1109/siu55565.2022.9864938
https://doi.org/10.1109/siu55565.2022.9864938
Autor:
Gökçe NUR YILMAZ, Gozde BOZDAGI AKAR
Publikováno v:
Volume: 15, Issue: 1 1-5
Türkiye Bilişim Vakfı Bilgisayar Bilimleri ve Mühendisliği Dergisi
Türkiye Bilişim Vakfı Bilgisayar Bilimleri ve Mühendisliği Dergisi
Günümüzdeki en revaçta araştırma alanlarından birisi kullanıcılara gelişmiş çoklu-ortam servisleri sağlayabilmek adına 3 Boyutlu (3B) video Kalite Deneyimini (KD) etkin olarak tahmin eden objektif metriklerin geliştirilmesidir. Fakat,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21b4abafa2a44f412ef06669e33cd234
https://dergipark.org.tr/tr/pub/tbbmd/issue/70571/1014412
https://dergipark.org.tr/tr/pub/tbbmd/issue/70571/1014412
Autor:
Gozde Bozdagi Akar, Gokce Nur Yilmaz
Publikováno v:
2021 6th International Conference on Computer Science and Engineering (UBMK).
In order to provide improved multimedia services to the end users, developing objective models efficiently predicting 3 Dimensional (3D) video Quality of Experience (QoE) can currently be considered as one of the most significant research areas. Neve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2fe2a8a3a2bc67edefa38c9ed22fc47a
https://doi.org/10.1109/ubmk52708.2021.9558955
https://doi.org/10.1109/ubmk52708.2021.9558955
Autor:
Savas Ozkan, N. Sinem Gezer, Dmitrii Lachinov, Debdoot Sheet, Fabian Isensee, Gozde Bozdagi Akar, M. Alper Selver, Soumick Chatterjee, Oliver Speck, A. Emre Kavur, Sinem Aslan, Josef Pauli, Oğuz Dicle, Gozde Unal, Pierre-Henri Conze, Andreas Nürnberger, Klaus H. Maier-Hein, Gurbandurdy Dovletov, Ronnie Rajan, Vladimir Groza, Rachana Sathish, Bora Baydar, Matthias Perkonigg, Shuo Han, Philipp Ernst, Duc Duy Pham, Mustafa Baris
Publikováno v:
Medical Image Analysis
Medical Image Analysis, Elsevier, 2021, 69, ⟨10.1016/j.media.2020.101950⟩
Medical Image Analysis, Elsevier, 2021, 69, ⟨10.1016/j.media.2020.101950⟩
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many years. In the last decade, intensive developments in deep learning (DL) introduced new state-of-the-art segmentation systems. Despite outperforming the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::062a182f507db13c73a8422353093c1a
https://hdl.handle.net/10278/3736173
https://hdl.handle.net/10278/3736173
Autor:
Gozde Bozdagi Akar, Mete Can Kaya
Publikováno v:
SIU
In this paper, we present a Unet architecture made of octave convolution for dental image segmentation problem. In this architecture, the requirements for memory and accuracy are significantly improved compared to previous works in the literature. Co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3c404803ba8cf4a3b7c8ab52752de4a8
https://doi.org/10.1109/siu49456.2020.9302495
https://doi.org/10.1109/siu49456.2020.9302495
Autor:
Savas Ozkan, Mustafa Baris, Gozde Bozdagi Akar, Çağlar Kılıkçıer, Ulaş Yüksel, M. Alper Selver, Naciye Sinem Gezer, Sahin Olut, Bora Baydar, Oğuz Dicle, A. Emre Kavur, Gozde Unal, Yusuf Huseyin Sahin
Purpose To compare the accuracy and repeatability of emerging machine learning based (i.e. deep) automatic segmentation algorithms with those of well-established semi-automatic (interactive) methods for determining liver volume in living liver transp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b11052d7b6da45edef43704acf6410dc
https://aperta.ulakbim.gov.tr/record/6871
https://aperta.ulakbim.gov.tr/record/6871
Autor:
Savas Ozkan, Gozde Bozdagi Akar
Publikováno v:
CVPR Workshops
Hyperspectral data provides rich information about a scene in terms of spectral details since it encapsulates measurements/observations from a wide large range of spectrum. To this end, it has been used in different problems mostly related to identif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1f827c5c06cbddb89b4ff1e2a20124e
https://doi.org/10.1109/cvprw.2019.00126
https://doi.org/10.1109/cvprw.2019.00126