Zobrazeno 1 - 10
of 478
pro vyhledávání: '"Tan Shan"'
Publikováno v:
BMC Musculoskeletal Disorders, Vol 24, Iss 1, Pp 1-7 (2023)
Abstract Objective This study aimed to investigate the techniques and indications of upper sacroiliac screw fixation for the dysmorphic sacrum. Methods The dysmorphic sacra were selected from 267 three-dimensional pelvic models. The dysmorphic sacra
Externí odkaz:
https://doaj.org/article/bf01b08bee9a4f43a881958d811d2e7b
Autor:
Cheng, Jun, Tan, Shan
Real-world noise removal is crucial in low-level computer vision. Due to the remarkable generation capabilities of diffusion models, recent attention has shifted towards leveraging diffusion priors for image restoration tasks. However, existing diffu
Externí odkaz:
http://arxiv.org/abs/2410.17521
Autor:
Lim, Soon Wei Daniel, Kee, Yong How, Smith, Scott Nicholas Allan, Tan, Shan Mei, Lim, An Eng, Yang, Yuansheng, Goh, Shireen
Inertial microfluidics have been limited to dilute particle concentrations due to defocusing at high particle concentrations. However, we observed a counterintuitive shift of focusing to the outer wall at high concentrations, which contradicts the ex
Externí odkaz:
http://arxiv.org/abs/2409.12488
Image denoising is a fundamental task in computer vision. While prevailing deep learning-based supervised and self-supervised methods have excelled in eliminating in-distribution noise, their susceptibility to out-of-distribution (OOD) noise remains
Externí odkaz:
http://arxiv.org/abs/2403.15132
Image denoising is a fundamental task in low-level computer vision. While recent deep learning-based image denoising methods have achieved impressive performance, they are black-box models and the underlying denoising principle remains unclear. In th
Externí odkaz:
http://arxiv.org/abs/2309.14755
During the process of computed tomography (CT), metallic implants often cause disruptive artifacts in the reconstructed images, impeding accurate diagnosis. Several supervised deep learning-based approaches have been proposed for reducing metal artif
Externí odkaz:
http://arxiv.org/abs/2308.16742
Real-world single image denoising is crucial and practical in computer vision. Bayesian inversions combined with score priors now have proven effective for single image denoising but are limited to white Gaussian noise. Moreover, applying existing sc
Externí odkaz:
http://arxiv.org/abs/2308.04682
Denoising low-dose computed tomography (CT) images is a critical task in medical image computing. Supervised deep learning-based approaches have made significant advancements in this area in recent years. However, these methods typically require pair
Externí odkaz:
http://arxiv.org/abs/2305.15887
Autor:
Pearce, Tim, Rashid, Tabish, Kanervisto, Anssi, Bignell, Dave, Sun, Mingfei, Georgescu, Raluca, Macua, Sergio Valcarcel, Tan, Shan Zheng, Momennejad, Ida, Hofmann, Katja, Devlin, Sam
Publikováno v:
ICLR 2023
Diffusion models have emerged as powerful generative models in the text-to-image domain. This paper studies their application as observation-to-action models for imitating human behaviour in sequential environments. Human behaviour is stochastic and
Externí odkaz:
http://arxiv.org/abs/2301.10677
Autor:
Yu, Bingcheng, Shi, Jiangjian, Li, Yiming, Tan, Shan, Cui, Yuqi, Meng, Fanqi, Wu, Huijue, Luo, Yanhong, Li, Dongmei, Meng, Qingbo
Operational stability of perovskite solar cells is remarkably influenced by the device temperature, therefore, decreasing the interior temperature of the device is one of the most effective approaches to prolong the service life. Herein, we introduce
Externí odkaz:
http://arxiv.org/abs/2205.13103