Zobrazeno 1 - 10
of 504
pro vyhledávání: '"Izadi, Mohammad"'
Diffusion models have recently shown strong potential in both music generation and music source separation tasks. Although in early stages, a trend is emerging towards integrating these tasks into a single framework, as both involve generating musica
Externí odkaz:
http://arxiv.org/abs/2409.12346
Diffusion models have shown promising results in cross-modal generation tasks involving audio and music, such as text-to-sound and text-to-music generation. These text-controlled music generation models typically focus on generating music by capturin
Externí odkaz:
http://arxiv.org/abs/2409.02845
If our noise-canceling headphones can understand our audio environments, they can then inform us of important sound events, tune equalization based on the types of content we listen to, and dynamically adjust noise cancellation parameters based on au
Externí odkaz:
http://arxiv.org/abs/2404.04386
Autor:
Karchkhadze, Tornike, Kavaki, Hassan Salami, Izadi, Mohammad Rasool, Irvin, Bryce, Kegler, Mikolaj, Hertz, Ari, Zhang, Shuo, Stamenovic, Marko
Publikováno v:
EUSIPCO 2024 Proceedings, ISBN: 978-9-4645-9361-7
Foley sound generation, the art of creating audio for multimedia, has recently seen notable advancements through text-conditioned latent diffusion models. These systems use multimodal text-audio representation models, such as Contrastive Language-Aud
Externí odkaz:
http://arxiv.org/abs/2403.12182
Efficient real-time traffic prediction is crucial for reducing transportation time. To predict traffic conditions, we employ a spatio-temporal graph neural network (ST-GNN) to model our real-time traffic data as temporal graphs. Despite its capabilit
Externí odkaz:
http://arxiv.org/abs/2401.11798
Text-to-image generation models have grown in popularity due to their ability to produce high-quality images from a text prompt. One use for this technology is to enable the creation of more accessible art creation software. In this paper, we documen
Externí odkaz:
http://arxiv.org/abs/2309.02402
Autor:
Srivastava, Hari Mohan, Methi, Giriraj, Kumar, Anil, Izadi, Mohammad, Mishra, Vishnu Narayan, Benhammouda, Brahim
The differential transform method is used to find numerical approximation of solution to a class of certain nonlinear differential algebraic equations. The method is based on Taylor's theorem. Coefficients of the Taylor series are determined by const
Externí odkaz:
http://arxiv.org/abs/2304.06856
Autor:
Shashaank, N, Banar, Berker, Izadi, Mohammad Rasool, Kemmerer, Jeremy, Zhang, Shuo, Huang, Chuan-Che
Modern noise-cancelling headphones have significantly improved users' auditory experiences by removing unwanted background noise, but they can also block out sounds that matter to users. Machine learning (ML) models for sound event detection (SED) an
Externí odkaz:
http://arxiv.org/abs/2303.07538
Autor:
Abdelkawy, M. A.1,2 (AUTHOR), Izadi, Mohammad3 (AUTHOR) izadi@uk.ac.ir, Adel, Waleed4,5 (AUTHOR)
Publikováno v:
Boundary Value Problems. 10/15/2024, Vol. 2024 Issue 1, p1-26. 26p.
Autor:
Parsamanesh, Mahmood1 mparsamanesh@tvu.ac.ir, Izadi, Mohammad2
Publikováno v:
Scientific Reports. 9/2/2024, Vol. 14 Issue 1, p1-12. 12p.