Zobrazeno 1 - 10
of 25 560
pro vyhledávání: '"Kim, Won"'
Autor:
Ding, Jiaqi, Dan, Tingting, Wei, Ziquan, Cho, Hyuna, Laurienti, Paul J., Kim, Won Hwa, Wu, Guorong
An unprecedented amount of existing functional Magnetic Resonance Imaging (fMRI) data provides a new opportunity to understand the relationship between functional fluctuation and human cognition/behavior using a data-driven approach. To that end, tre
Externí odkaz:
http://arxiv.org/abs/2409.11377
Autor:
Elkoumy, Ahmed, Rück, Andreas, Kim, Won-Keun, Abdel-Wahab, Mohamed, Abdelshafy, Mahmoud, De Backer, Ole, Elzomor, Hesham, Hengstenberg, Christian, Mohamed, Sameh K., Saleh, Nawzad, Arsang-Jang, Shahram, Bjursten, Henrik, Simpkin, Andrew, Meduri, Christopher U., Soliman, Osama
(1) Background: Hemodynamic assessment of prosthetic heart valves using conventional 2D transthoracic Echocardiography-Doppler (2D-TTE) has limitations. Of those, left ventricular outflow tract (LVOT) area measurement is one of the major limitations
Externí odkaz:
https://ul.qucosa.de/id/qucosa%3A91591
https://ul.qucosa.de/api/qucosa%3A91591/attachment/ATT-0/
https://ul.qucosa.de/api/qucosa%3A91591/attachment/ATT-0/
In this work, we introduce Mask-JEPA, a self-supervised learning framework tailored for mask classification architectures (MCA), to overcome the traditional constraints associated with training segmentation models. Mask-JEPA combines a Joint Embeddin
Externí odkaz:
http://arxiv.org/abs/2407.10733
The proliferation of edge devices necessitates efficient computational architectures for lightweight tasks, particularly deep neural network (DNN) inference. Traditional NPUs, though effective for such operations, face challenges in power, cost, and
Externí odkaz:
http://arxiv.org/abs/2407.02622
Recent experiments have shown that metachronal waves (MCWs) can emerge from a chain of symmetrically beating nematodes aligned at the edge of sessile droplets. Our study, employing a coupled elastohydrodynamic model of active filaments, elucidates th
Externí odkaz:
http://arxiv.org/abs/2406.18823
A Marked Temporal Point Process (MTPP) is a stochastic process whose realization is a set of event-time data. MTPP is often used to understand complex dynamics of asynchronous temporal events such as money transaction, social media, healthcare, etc.
Externí odkaz:
http://arxiv.org/abs/2406.06149
The human brain is a complex inter-wired system that emerges spontaneous functional fluctuations. In spite of tremendous success in the experimental neuroscience field, a system-level understanding of how brain anatomy supports various neural activit
Externí odkaz:
http://arxiv.org/abs/2405.16357
In Fringe Projection Profilometry (FPP), achieving robust and accurate 3D reconstruction with a limited number of fringe patterns remains a challenge in structured light 3D imaging. Conventional methods require a set of fringe images, but using only
Externí odkaz:
http://arxiv.org/abs/2402.00977
Domain shift occurs when training (source) and test (target) data diverge in their distribution. Source-Free Domain Adaptation (SFDA) addresses this domain shift problem, aiming to adopt a trained model on the source domain to the target domain in a
Externí odkaz:
http://arxiv.org/abs/2401.14587
Various Graph Neural Networks (GNNs) have been successful in analyzing data in non-Euclidean spaces, however, they have limitations such as oversmoothing, i.e., information becomes excessively averaged as the number of hidden layers increases. The is
Externí odkaz:
http://arxiv.org/abs/2401.11840