Zobrazeno 1 - 10
of 853
pro vyhledávání: '"Yavuz Mehmet"'
Publikováno v:
Open Physics, Vol 20, Iss 1, Pp 1127-1141 (2022)
The current work is devoted to introduce a novel thermoelastic heat conduction model where the Moore-Gibson-Thompson (MGT) equation describes the heat equation. The constructed model is characterized by allowing limited velocities of heat wave propag
Externí odkaz:
https://doaj.org/article/15d21621ce4a4b83bca0a1b847d5d34b
Autor:
Yavuz, Mehmet Can, Yang, Yang
In biomedical imaging analysis, the dichotomy between 2D and 3D data presents a significant challenge. While 3D volumes offer superior real-world applicability, they are less available for each modality and not easy to train in large scale, whereas 2
Externí odkaz:
http://arxiv.org/abs/2411.02441
Autor:
Liu, Jie, Zhang, Yixiao, Wang, Kang, Yavuz, Mehmet Can, Chen, Xiaoxi, Yuan, Yixuan, Li, Haoliang, Yang, Yang, Yuille, Alan, Tang, Yucheng, Zhou, Zongwei
The advancement of artificial intelligence (AI) for organ segmentation and tumor detection is propelled by the growing availability of computed tomography (CT) datasets with detailed, per-voxel annotations. However, these AI models often struggle wit
Externí odkaz:
http://arxiv.org/abs/2405.18356
Autor:
Yavuz, Mehmet Can, Yang, Yang
Deep learning classifiers face significant challenges when dealing with heterogeneous multi-modal and multi-organ biomedical datasets. The low-level feature distinguishability limited to imaging-modality hinders the classifiers' ability to learn high
Externí odkaz:
http://arxiv.org/abs/2406.14568
Private network deployment is gaining momentum in warehouses, retail, automation, health care, and many such use cases to guarantee mission-critical services with less latency. Guaranteeing the delay-sensitive application in Wi-Fi is always challengi
Externí odkaz:
http://arxiv.org/abs/2312.15108
Autor:
Yavuz, Mehmet Can, Yanikoglu, Berrin
Learning a discriminative semantic space using unlabelled and noisy data remains unaddressed in a multi-label setting. We present a contrastive self-supervised learning method which is robust to data noise, grounded in the domain of variational metho
Externí odkaz:
http://arxiv.org/abs/2312.00824
The 3.7 - 3.98 GHz frequency band (also known as C-band) was recently allocated in the US for the deployment of 5G cellular services. Prior to this, the lower adjacent band, 3.55 - 3.7 GHz, had been allocated to Citizens Broadband Radio Service (CBRS
Externí odkaz:
http://arxiv.org/abs/2304.07690
Autor:
Evirgen Fırat, Yavuz Mehmet
Publikováno v:
ITM Web of Conferences, Vol 22, p 01009 (2018)
In this study, a fractional mathematical model with steepest descent direction is proposed to find optimal solutions for a class of nonlinear programming problem. In this sense, Caputo-Fabrizio derivative is adapted to the mathematical model. To demo
Externí odkaz:
https://doaj.org/article/de757d26d2494931b0fe6f43b2be5c62
Autor:
Yavuz Mehmet, Özdemir Necati
Publikováno v:
ITM Web of Conferences, Vol 22, p 01045 (2018)
In this study, we have obtained analytical solutions of fractional Cauchy problem by using q-Homotopy Analysis Method (q-HAM) featuring conformable derivative. We have considered different situations according to the homogeneity and linearity of the
Externí odkaz:
https://doaj.org/article/3bb03c66b72149e69e10877a1913528a