Zobrazeno 1 - 10
of 428
pro vyhledávání: '"Prazak, P"'
We present a new method to bake classical facial animation blendshapes into a fast linear blend skinning representation. Previous work explored skinning decomposition methods that approximate general animated meshes using a dense set of bone transfor
Externí odkaz:
http://arxiv.org/abs/2406.11597
Autor:
Pražák, Dalibor, Zelina, Michael
We consider evolutionary Stokes system, coupled with the so-called dynamic boundary condition, in the simple geometry of $d$-dimensional half-space. Using the Fourier transform, we obtain an explicit formula for the resolvent. Maximal regularity esti
Externí odkaz:
http://arxiv.org/abs/2312.04478
Autor:
Přibáň, Pavel, Pražák, Ondřej
This paper presents a series of approaches aimed at enhancing the performance of Aspect-Based Sentiment Analysis (ABSA) by utilizing extracted semantic information from a Semantic Role Labeling (SRL) model. We propose a novel end-to-end Semantic Role
Externí odkaz:
http://arxiv.org/abs/2307.14785
Autor:
Pražák, Dalibor, Zelina, Michael
We consider incompressible Navier-Stokes equations in a bounded 2D domain, complete with the so-called dynamic slip boundary conditions. Assuming that the data are regular, we show that weak solutions are strong. As an application, we provide an expl
Externí odkaz:
http://arxiv.org/abs/2307.12413
Autor:
Prazak, Dalibor, Priyasad, Buddhika
We consider non-Newtonian incompressible 3D fluid of Ladyzhenskaya type, in the setting of the dynamic boundary condition. Assuming sufficient growth rate of the stress tensor with respect to the velocity gradient, we establish explicit dimension est
Externí odkaz:
http://arxiv.org/abs/2301.08112
Autor:
Olena Rogulska, Irena Vackova, Simon Prazak, Karolina Turnovcova, Sarka Kubinova, Lucie Bacakova, Pavla Jendelova, Yuriy Petrenko
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract The widespread use of multipotent mesenchymal stromal cell-derived secretome (MSC-sec) requires optimal preservation methods. Lyophilization offers benefits like concentrating the secretome, reducing the storage volume, and making storage co
Externí odkaz:
https://doaj.org/article/b69cd7bdb7c84d20946c5b430b7abecd
Autor:
Hannah Wozniak, Alexis Tabah, François Barbier, Stéphane Ruckly, Ambre Loiodice, Murat Akova, Marc Leone, Andrew Conway Morris, Matteo Bassetti, Kostoula Arvaniti, Ricard Ferrer, Liesbet de Bus, Jose Artur Paiva, Hendrik Bracht, Adam Mikstacki, Adel Alsisi, Liana Valeanu, Josef Prazak, Jean-François Timsit, Niccolò Buetti, on behalf of the EUROBACT-2 Study Group, ESICM, ESCMID ESGCIP and the OUTCOMEREA Network
Publikováno v:
Annals of Intensive Care, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Background Hospital-acquired bloodstream infections are common in the intensive care unit (ICU) and have a high mortality rate. Patients with cirrhosis are especially susceptible to infections, yet there is a knowledge gap in the epidemiolog
Externí odkaz:
https://doaj.org/article/fe09467495ba4b089af4f17200897ee6
Publikováno v:
Emerging Science Journal, Vol 8, Iss 2, Pp 394-406 (2024)
The localization accuracy of a fingerprint-based localization system is dependent on several factors, one of which is the accuracy and efficiency at which the fingerprint database is clustered. Most highly efficient and accurate clustering algorithms
Externí odkaz:
https://doaj.org/article/cf1a5a3d04c64ffc916c1d93ef50689a
Publikováno v:
\v{S}vec, J., \v{S}m\'idl, L., Psutka, J.V., Pra\v{z}\'ak, A. (2021) Spoken Term Detection and Relevance Score Estimation Using Dot-Product of Pronunciation Embeddings. Proc. Interspeech 2021, 4398-4402
The paper describes a novel approach to Spoken Term Detection (STD) in large spoken archives using deep LSTM networks. The work is based on the previous approach of using Siamese neural networks for STD and naturally extends it to directly localize a
Externí odkaz:
http://arxiv.org/abs/2210.11895
Autor:
Pražák, Ondřej, Konopík, Miloslav
This paper describes our approach to the CRAC 2022 Shared Task on Multilingual Coreference Resolution. Our model is based on a state-of-the-art end-to-end coreference resolution system. Apart from joined multilingual training, we improved our results
Externí odkaz:
http://arxiv.org/abs/2209.12516