Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Dey, Raunak"'
Autor:
Manikandan, Sreekanth K, Das, Biswajit, Dey, Raunak, Kundu, Avijit, Banerjee, Ayan, Krishnamurthy, Supriya
Measurements of any property of a microscopic system are bound to show significant deviations from the average, due to thermal fluctuations. For time-integrated currents such as heat, work or entropy production in a steady state, it is in fact known
Externí odkaz:
http://arxiv.org/abs/2201.06563
In this paper we consider the problem of unsupervised anomaly segmentation in medical images, which has attracted increasing attention in recent years due to the expensive pixel-level annotations from experts and the existence of a large amount of un
Externí odkaz:
http://arxiv.org/abs/2112.09135
A large number of processes in the mesoscopic world occur out of equilibrium, where the time course of a system evolution becomes immensely important since it is driven principally by dissipative effects. Non-equilibrium steady states (NESS) represen
Externí odkaz:
http://arxiv.org/abs/2104.00127
We employ multiple sinusoid modulated optical tweezers to measure the frequency dependent rheological parameters of a linear viscoelastic fluid over five decades of frequency in a single shot, hitherto not achieved using active microrheology alone. T
Externí odkaz:
http://arxiv.org/abs/2103.04093
Autor:
Dey, Raunak, Hong, Yi
We introduce a neural network framework, utilizing adversarial learning to partition an image into two cuts, with one cut falling into a reference distribution provided by the user. This concept tackles the task of unsupervised anomaly segmentation,
Externí odkaz:
http://arxiv.org/abs/2103.03664
Autor:
Dey, Raunak, Hong, Yi
Automatic liver lesion segmentation is a challenging task while having a significant impact on assisting medical professionals in the designing of effective treatment and planning proper care. In this paper we propose a cascaded system that combines
Externí odkaz:
http://arxiv.org/abs/1909.04797
Publikováno v:
In Computers and Education: Artificial Intelligence 2023 5
Autor:
Dey, Raunak, Hong, Yi
Brain extraction is a fundamental step for most brain imaging studies. In this paper, we investigate the problem of skull stripping and propose complementary segmentation networks (CompNets) to accurately extract the brain from T1-weighted MRI scans,
Externí odkaz:
http://arxiv.org/abs/1804.00521
Lung cancer is the leading cause of cancer-related death worldwide. Early diagnosis of pulmonary nodules in Computed Tomography (CT) chest scans provides an opportunity for designing effective treatment and making financial and care plans. In this pa
Externí odkaz:
http://arxiv.org/abs/1803.07192
Autor:
Setayeshfar, Omid, Subramani, Karthika, Yuan, Xingzi, Dey, Raunak, Hong, Dezhi, Kim, In Kee, Lee, Kyu Hyung
Publikováno v:
In Pervasive and Mobile Computing September 2022 85