Zobrazeno 1 - 10
of 10 658
pro vyhledávání: '"Yu Zhen"'
The neural radiance field (NERF) advocates learning the continuous representation of 3D geometry through a multilayer perceptron (MLP). By integrating this into a generative model, the generative neural radiance field (GRAF) is capable of producing i
Externí odkaz:
http://arxiv.org/abs/2412.00754
Autor:
Yan, Siyuan, Yu, Zhen, Primiero, Clare, Vico-Alonso, Cristina, Wang, Zhonghua, Yang, Litao, Tschandl, Philipp, Hu, Ming, Tan, Gin, Tang, Vincent, Ng, Aik Beng, Powell, David, Bonnington, Paul, See, Simon, Janda, Monika, Mar, Victoria, Kittler, Harald, Soyer, H. Peter, Ge, Zongyuan
Diagnosing and treating skin diseases require advanced visual skills across multiple domains and the ability to synthesize information from various imaging modalities. Current deep learning models, while effective at specific tasks such as diagnosing
Externí odkaz:
http://arxiv.org/abs/2410.15038
Autor:
Zhang, Xin, Mehta, Deval, Hu, Yanan, Zhu, Chao, Darby, David, Yu, Zhen, Merlo, Daniel, Gresle, Melissa, Van Der Walt, Anneke, Butzkueven, Helmut, Ge, Zongyuan
Survival analysis holds a crucial role across diverse disciplines, such as economics, engineering and healthcare. It empowers researchers to analyze both time-invariant and time-varying data, encompassing phenomena like customer churn, material degra
Externí odkaz:
http://arxiv.org/abs/2409.06209
Vision-language foundation models like CLIP have shown impressive zero-shot generalization, but finetuning on downstream datasets can cause overfitting and loss of its generalization ability on unseen domains. Although collecting additional data from
Externí odkaz:
http://arxiv.org/abs/2405.02586
In the problem of quickest change detection (QCD), a change occurs at some unknown time in the distribution of a sequence of independent observations. This work studies a QCD problem where the change is either a bad change, which we aim to detect, or
Externí odkaz:
http://arxiv.org/abs/2405.00842
It is essential but challenging to share medical image datasets due to privacy issues, which prohibit building foundation models and knowledge transfer. In this paper, we propose a novel dataset distillation method to condense the original medical im
Externí odkaz:
http://arxiv.org/abs/2403.13469
Autor:
Yan, Siyuan, Liu, Chi, Yu, Zhen, Ju, Lie, Mahapatra, Dwarikanath, Betz-Stablein, Brigid, Mar, Victoria, Janda, Monika, Soyer, Peter, Ge, Zongyuan
Deep learning models for medical image analysis easily suffer from distribution shifts caused by dataset artifacts bias, camera variations, differences in the imaging station, etc., leading to unreliable diagnoses in real-world clinical settings. Dom
Externí odkaz:
http://arxiv.org/abs/2401.03002
Publikováno v:
Stem Cell Research & Therapy, Vol 15, Iss 1, Pp 1-19 (2024)
Abstract Background Stem cell transplantation has been regarded as a promising therapeutic strategy for myocardial regeneration after myocardial infarction (MI). However, the survival and differentiation of the transplanted stem cells in the hostile
Externí odkaz:
https://doaj.org/article/6df1347b823d4a67a2237cd07282b13a
Publikováno v:
BMC Nephrology, Vol 25, Iss 1, Pp 1-10 (2024)
Abstract Backgound People with diabetes are much more likely to develop acute kidney injury (AKI) than people without diabetes. Low 25-hydroxy-vitamin D [25(OH)D] concentrations increased the risk of AKI in specific populations. Few studies have expl
Externí odkaz:
https://doaj.org/article/cffab97d641f4d64aa319533f1effbe5
Effective resource allocation in sensor networks, IoT systems, and distributed computing is essential for applications such as environmental monitoring, surveillance, and smart infrastructure. Sensors or agents must optimize their resource allocation
Externí odkaz:
http://arxiv.org/abs/2307.06442