Zobrazeno 1 - 10
of 19 401
pro vyhledávání: '"Woo, Jin"'
Autor:
Jost, Daniel, Lomeli, Eder G., Kim, Woo Jin, Been, Emily M., Rossi, Matteo, Agrestini, Stefano, Zhou, Kejin, Jia, Chunjing, Moritz, Brian, Shen, Zhi-Xun, Hwang, Harold Y., Devereaux, Thomas P., Lee, Wei-Sheng
The layered cobaltate CaCoO$_2$ exhibits a unique herringbone-like structure. Serving as a potential prototype for a new class of complex lattice patterns, we study the properties of CaCoO$_2$ using X-ray absorption spectroscopy (XAS) and resonant in
Externí odkaz:
http://arxiv.org/abs/2409.07705
Autor:
Bransby, Kit M., Kim, Woo-jin Cho, Oliveira, Jorge, Thorley, Alex, Beqiri, Arian, Gomez, Alberto, Chartsias, Agisilaos
Building an echocardiography view classifier that maintains performance in real-life cases requires diverse multi-site data, and frequent updates with newly available data to mitigate model drift. Simply fine-tuning on new datasets results in "catast
Externí odkaz:
http://arxiv.org/abs/2407.21577
Self-supervised multi-frame monocular depth estimation relies on the geometric consistency between successive frames under the assumption of a static scene. However, the presence of moving objects in dynamic scenes introduces inevitable inconsistenci
Externí odkaz:
http://arxiv.org/abs/2407.09303
As Deep Neural Networks (DNNs) rapidly advance in various fields, including speech verification, they typically involve high computational costs and substantial memory consumption, which can be challenging to manage on mobile systems. Quantization of
Externí odkaz:
http://arxiv.org/abs/2407.08991
Autor:
Bransby, Kit Mills, Beqiri, Arian, Kim, Woo-Jin Cho, Oliveira, Jorge, Chartsias, Agisilaos, Gomez, Alberto
Neural networks can learn spurious correlations that lead to the correct prediction in a validation set, but generalise poorly because the predictions are right for the wrong reason. This undesired learning of naive shortcuts (Clever Hans effect) can
Externí odkaz:
http://arxiv.org/abs/2406.19148
Speaker-Independent Acoustic-to-Articulatory Inversion through Multi-Channel Attention Discriminator
Autor:
Chung, Woo-Jin, Kang, Hong-Goo
We present a novel speaker-independent acoustic-to-articulatory inversion (AAI) model, overcoming the limitations observed in conventional AAI models that rely on acoustic features derived from restricted datasets. To address these challenges, we lev
Externí odkaz:
http://arxiv.org/abs/2406.17329
Deep learning models for semantic segmentation often experience performance degradation when deployed to unseen target domains unidentified during the training phase. This is mainly due to variations in image texture (\ie style) from different data s
Externí odkaz:
http://arxiv.org/abs/2403.06122
Autor:
Pezzè, Luca, Xhani, Klejdja, Daix, Cyprien, Grani, Nicola, Donelli, Beatrice, Scazza, Francesco, Hernandez-Rajkov, Diego, Kwon, Woo Jin, Del Pace, Giulia, Roati, Giacomo
Arrays of Josephson junctions are at the forefront of research on quantum circuitry for quantum computing, simulation and metrology. They provide a testing bed for exploring a variety of fundamental physical effects where macroscopic phase coherence,
Externí odkaz:
http://arxiv.org/abs/2311.05523
This report describes our submission to BHI 2023 Data Competition: Sensor challenge. Our Audio Alchemists team designed an acoustic-based COVID-19 diagnosis system, Cough to COVID-19 (C2C), and won the 1st place in the challenge. C2C involves three k
Externí odkaz:
http://arxiv.org/abs/2311.00364
Publikováno v:
Acta Pharmaceutica Sinica B, Vol 14, Iss 12, Pp 5451-5463 (2024)
The pathophysiology of sepsis is characterized by a systemic inflammatory response to infection; however, the cytokine blockade that targets a specific early inflammatory mediator, such as tumor necrosis factor, has shown disappointing results in cli
Externí odkaz:
https://doaj.org/article/98d4ee0fd71b4942a5258ba3ae527783
