Zobrazeno 1 - 10
of 75 467
pro vyhledávání: '"vector quantization"'
Autor:
Shaffiee Haghshenas, Sina1 (AUTHOR) giuseppe.guido@unical.it, Guido, Giuseppe1 (AUTHOR), Shaffiee Haghshenas, Sami1 (AUTHOR), Astarita, Vittorio1 (AUTHOR)
Publikováno v:
AI. Sep2024, Vol. 5 Issue 3, p1095-1110. 16p.
Autor:
Lin, Yijie1 (AUTHOR) p1263670@o365.fcu.edu.tw, Liu, Jui-Chuan1 (AUTHOR) p1200318@o365.fcu.edu.tw, Chang, Ching-Chun2 (AUTHOR) ccc@fcu.edu.tw, Chang, Chin-Chen1 (AUTHOR) ccc@o365.fcu.edu.tw
Publikováno v:
Mathematics (2227-7390). May2024, Vol. 12 Issue 9, p1332. 14p.
Autor:
Severo, Verusca1 (AUTHOR) rshc@poli.br, Ferreira, Felipe B. S.2 (AUTHOR) felipe.bsferreira@ufrpe.br, Spencer, Rodrigo1 (AUTHOR) artn@poli.br, Nascimento, Arthur1 (AUTHOR) madeiro@poli.br, Madeiro, Francisco1 (AUTHOR)
Publikováno v:
Sensors (14248220). Apr2024, Vol. 24 Issue 8, p2606. 38p.
Current neural audio codecs typically use residual vector quantization (RVQ) to discretize speech signals. However, they often experience codebook collapse, which reduces the effective codebook size and leads to suboptimal performance. To address thi
Externí odkaz:
http://arxiv.org/abs/2410.12359
Autor:
Fifty, Christopher, Junkins, Ronald G., Duan, Dennis, Iger, Aniketh, Liu, Jerry W., Amid, Ehsan, Thrun, Sebastian, Ré, Christopher
Vector Quantized Variational AutoEncoders (VQ-VAEs) are designed to compress a continuous input to a discrete latent space and reconstruct it with minimal distortion. They operate by maintaining a set of vectors -- often referred to as the codebook -
Externí odkaz:
http://arxiv.org/abs/2410.06424
Built upon vector quantization (VQ), discrete audio codec models have achieved great success in audio compression and auto-regressive audio generation. However, existing models face substantial challenges in perceptual quality and signal distortion,
Externí odkaz:
http://arxiv.org/abs/2409.12717
In response to the rapid growth of global videomtraffic and the limitations of traditional wireless transmission systems, we propose a novel dual-stage vector quantization framework, VQ-DeepVSC, tailored to enhance video transmission over wireless ch
Externí odkaz:
http://arxiv.org/abs/2409.03393
Normalizing flows, a category of probabilistic models famed for their capabilities in modeling complex data distributions, have exhibited remarkable efficacy in unsupervised anomaly detection. This paper explores the potential of normalizing flows in
Externí odkaz:
http://arxiv.org/abs/2409.00942
The Diffusion Transformers Models (DiTs) have transitioned the network architecture from traditional UNets to transformers, demonstrating exceptional capabilities in image generation. Although DiTs have been widely applied to high-definition video ge
Externí odkaz:
http://arxiv.org/abs/2408.17131
Autor:
Enck, David1 (AUTHOR) david.enck@ttu.edu, Beruvides, Mario1 (AUTHOR) mario.beruvides@ttu.edu, Tercero-Gómez, Víctor G.2 (AUTHOR) victor.tercero@tec.mx, Cordero-Franco, Alvaro E.3 (AUTHOR) alvaro.corderofr@uanl.edu.mx
Publikováno v:
Mathematics (2227-7390). Mar2024, Vol. 12 Issue 5, p678. 15p.