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pro vyhledávání: '"Volkan P"'
Publikováno v:
Asian Journal of Surgery, Vol 47, Iss 12, Pp 5131-5136 (2024)
Objective: To compare the effectiveness of combined (indocyanine green [ICG]+ blue dye) tracing versus blue dye alone in guiding sentinel lymph node biopsy (SLNB) in breast cancer. Methods: A total of 112 female patients (mean ± SD age: 51.9 ± 11.9
Externí odkaz:
https://doaj.org/article/881e7abd16f947f88d0b3e9cb6c6fcf1
Autor:
Lastovina, Tatiana, Usoltsev, Oleg, Isik, Furkan, Budnyk, Andriy, Harfouche, Messaoud, Canimkurbey, Betul, Demir, Hilmi Volkan
We report on a systematic study of the Cd, Zn, Se, and S elemental distributions across the interfaces in CdSe/Cd1-xZnxS core-shell and CdSe/CdS/Cd1-xZnxS core-crown-shell quantum wells with the CdSe core thickness ranging from 3.5 to 5.5 ML. By proc
Externí odkaz:
http://arxiv.org/abs/2412.18795
Autor:
Sevinc, Volkan, Tsagris, Michail
Not many tests exist for testing the equality for two or more multivariate distributions with compositional data, perhaps due to their constrained sample space. At the moment, there is only one test suggested that relies upon random projections. We p
Externí odkaz:
http://arxiv.org/abs/2412.05199
The Last Mile to Supervised Performance: Semi-Supervised Domain Adaptation for Semantic Segmentation
Supervised deep learning requires massive labeled datasets, but obtaining annotations is not always easy or possible, especially for dense tasks like semantic segmentation. To overcome this issue, numerous works explore Unsupervised Domain Adaptation
Externí odkaz:
http://arxiv.org/abs/2411.18728
The widespread adoption of deep learning across various industries has introduced substantial challenges, particularly in terms of model explainability and security. The inherent complexity of deep learning models, while contributing to their effecti
Externí odkaz:
http://arxiv.org/abs/2411.11200
Large vision-language models (VLLMs) exhibit promising capabilities for processing multi-modal tasks across various application scenarios. However, their emergence also raises significant data security concerns, given the potential inclusion of sensi
Externí odkaz:
http://arxiv.org/abs/2411.02902
Autor:
Cem Gürler, Volkan Polat
Publikováno v:
Revista Brasileira de Futsal e Futebol, Vol 13, Iss 52, Pp 118-124 (2021)
Technology is now widely used in sports. One of those technology is video assistant referee (VAR) system. After being officially used in 2018 World Cup for the first time, major leagues started using VAR from the 2018/2019 season. In this study, 94 m
Externí odkaz:
https://doaj.org/article/13c111a8436e4432b9985ebfd98a70e6
Sharpness Aware Minimization (SAM) enhances performance across various neural architectures and datasets. As models are continually scaled up to improve performance, a rigorous understanding of SAM's scaling behaviour is paramount. To this end, we st
Externí odkaz:
http://arxiv.org/abs/2411.00075
Autor:
Bu, Zhiqi, Jin, Xiaomeng, Vinzamuri, Bhanukiran, Ramakrishna, Anil, Chang, Kai-Wei, Cevher, Volkan, Hong, Mingyi
Machine unlearning has been used to remove unwanted knowledge acquired by large language models (LLMs). In this paper, we examine machine unlearning from an optimization perspective, framing it as a regularized multi-task optimization problem, where
Externí odkaz:
http://arxiv.org/abs/2410.22086
Sharpness-aware minimization (SAM) has been shown to improve the generalization of neural networks. However, each SAM update requires \emph{sequentially} computing two gradients, effectively doubling the per-iteration cost compared to base optimizers
Externí odkaz:
http://arxiv.org/abs/2410.10683