Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Çiçek, Özgün"'
Autor:
Gómez-de-Mariscal, Estibaliz, Jayatilaka, Hasini, Çiçek, Özgün, Brox, Thomas, Wirtz, Denis, Muñoz-Barrutia, Arrate
Studying cell morphology changes in time is critical to understanding cell migration mechanisms. In this work, we present a deep learning-based workflow to segment cancer cells embedded in 3D collagen matrices and imaged with phase-contrast microscop
Externí odkaz:
http://arxiv.org/abs/2112.08817
Publikováno v:
ICCV 2021
Predicting the states of dynamic traffic actors into the future is important for autonomous systems to operate safelyand efficiently. Remarkably, the most critical scenarios aremuch less frequent and more complex than the uncriticalones. Therefore, u
Externí odkaz:
http://arxiv.org/abs/2103.12474
Deploying off-the-shelf segmentation networks on biomedical data has become common practice, yet if structures of interest in an image sequence are visible only temporarily, existing frame-by-frame methods fail. In this paper, we provide a solution t
Externí odkaz:
http://arxiv.org/abs/2011.10486
In this paper, we investigate the problem of anticipating future dynamics, particularly the future location of other vehicles and pedestrians, in the view of a moving vehicle. We approach two fundamental challenges: (1) the partial visibility due to
Externí odkaz:
http://arxiv.org/abs/2006.04700
Active learning aims to reduce the high labeling cost involved in training machine learning models on large datasets by efficiently labeling only the most informative samples. Recently, deep active learning has shown success on various tasks. However
Externí odkaz:
http://arxiv.org/abs/1912.05361
Future prediction is a fundamental principle of intelligence that helps plan actions and avoid possible dangers. As the future is uncertain to a large extent, modeling the uncertainty and multimodality of the future states is of great relevance. Exis
Externí odkaz:
http://arxiv.org/abs/1906.03631
Autor:
Zolfaghari, Mohammadreza, Çiçek, Özgün, Ali, Syed Mohsin, Mahdisoltani, Farzaneh, Zhang, Can, Brox, Thomas
Foreseeing the future is one of the key factors of intelligence. It involves understanding of the past and current environment as well as decent experience of its possible dynamics. In this work, we address future prediction at the abstract level of
Externí odkaz:
http://arxiv.org/abs/1905.03578
Autor:
Ilg, Eddy, Çiçek, Özgün, Galesso, Silvio, Klein, Aaron, Makansi, Osama, Hutter, Frank, Brox, Thomas
Optical flow estimation can be formulated as an end-to-end supervised learning problem, which yields estimates with a superior accuracy-runtime tradeoff compared to alternative methodology. In this paper, we make such networks estimate their local un
Externí odkaz:
http://arxiv.org/abs/1802.07095
This paper introduces a network for volumetric segmentation that learns from sparsely annotated volumetric images. We outline two attractive use cases of this method: (1) In a semi-automated setup, the user annotates some slices in the volume to be s
Externí odkaz:
http://arxiv.org/abs/1606.06650
EVALUATION OF PROGNOSIS AND RISK FACTORS OF DIFFERENTIATED THYROID CANCER IN A GERIATRIC POPULATION.
Autor:
ALTAY, Feride Pınar1 fpaltay@gmail.com, ÇİÇEK, Özgün2, DEMİRKAN, Ecem2, TAŞKALDIRAN, Işılay1, BOZKUŞ, Yusuf1, TURHAN İYİDİR, Özlem1, NAR, Aslı1, BAŞÇIL TÜTÜNCÜ, Neslihan1
Publikováno v:
Turkish Journal of Geriatrics / Türk Geriatri Dergisi. 2023, Vol. 26 Issue 2, p118-123. 6p.
