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Akademický článek
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Akademický článek
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Autor:
Willis, Royce, Lynch, David, Peddell, Lewes, Yeigh, Tony, Woolcott, Geoff, Bui, Vinh, Boyd, Wendy, Ellis, David, Markopoulos, Christos, James, Sarah
Publikováno v:
Mathematics Education Research Journal; 2023Suppl1, Vol. 35, p107-132, 26p
Autor:
Hana Lacová
Publikováno v:
Slovenska Literatura, Vol 69, Iss 3, Pp 304-306 (2022)
AYERS, David – HJARTARSON, Benedikt – HUTTUNEN, Tomi – VEIVO, Harri, ed.: Utopia. The Avant-garde, Modernism and (Im)Possible Life.
Externí odkaz:
https://doaj.org/article/923f3680024643519836ea6a24575114
Federated learning (FL) has become one of the key methods for privacy-preserving collaborative learning, as it enables the transfer of models without requiring local data exchange. Within the FL framework, an aggregation algorithm is recognized as on
Externí odkaz:
http://arxiv.org/abs/2411.07816
Current speech deepfake detection approaches perform satisfactorily against known adversaries; however, generalization to unseen attacks remains an open challenge. The proliferation of speech deepfakes on social media underscores the need for systems
Externí odkaz:
http://arxiv.org/abs/2410.20578
Event cameras, inspired by biological vision, are asynchronous sensors that detect changes in brightness, offering notable advantages in environments characterized by high-speed motion, low lighting, or wide dynamic range. These distinctive propertie
Externí odkaz:
http://arxiv.org/abs/2410.15480
Autor:
Verdera, Jordina Aviles, Silva, Sara Neves, Tomi-Tricot, Raphael, Hall, Megan, Story, Lisa, Malik, Shaihan J, Hajnal, Joseph V, Rutherford, Mary A, Hutter, Jana
Purpose: To provide real-time quantitative organ-specific information - specifically placental and brain T2* - to allow optimization of the MR examination to the individual patient. Methods: A FIRE-based real-time setup segmenting placenta and fetal
Externí odkaz:
http://arxiv.org/abs/2409.16878
In recent years, Light Detection and Ranging (LiDAR) technology, a critical sensor in robotics and autonomous systems, has seen significant advancements. These improvements include enhanced resolution of point clouds and the capability to provide 360
Externí odkaz:
http://arxiv.org/abs/2409.11532
We propose a novel approach for spoofed speech characterization through explainable probabilistic attribute embeddings. In contrast to high-dimensional raw embeddings extracted from a spoofing countermeasure (CM) whose dimensions are not easy to inte
Externí odkaz:
http://arxiv.org/abs/2409.11027