Zobrazeno 1 - 10
of 60 504
pro vyhledávání: '"A. Nakata"'
Autor:
Nakata, Atsuya, Yamanaka, Takao
Omni-directional images have been increasingly used in various applications, including virtual reality and SNS (Social Networking Services). However, their availability is comparatively limited in contrast to normal field of view (NFoV) images, since
Externí odkaz:
http://arxiv.org/abs/2409.09969
We present our system (denoted as T05) for the VoiceMOS Challenge (VMC) 2024. Our system was designed for the VMC 2024 Track 1, which focused on the accurate prediction of naturalness mean opinion score (MOS) for high-quality synthetic speech. In add
Externí odkaz:
http://arxiv.org/abs/2409.09305
Autor:
Takahashi, Ryunosuke, Guen, Yann Le, Nakata, Suguru, Igarashi, Junta, Hohlfeld, Julius, Malinowski, Grégory, Lingling, Xie, Daisuke, Kan, Shimakawa, Yuichi, Mangin, Stéphane, Wadati, Hiroki
All-optical switching (AOS) involves manipulating magnetization using only pulsed laser, presenting a promising approach for next-generation magnetic recording devices. NiCo2O4 (NCO) thin films, a rare-earth-free ferrimagnetic oxide, exhibit a high C
Externí odkaz:
http://arxiv.org/abs/2409.01615
In this paper, we rethink sparse lexical representations for image retrieval. By utilizing multi-modal large language models (M-LLMs) that support visual prompting, we can extract image features and convert them into textual data, enabling us to util
Externí odkaz:
http://arxiv.org/abs/2408.16296
Publikováno v:
28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7-10, 2024, Proceedings, Part I, pp 209-220
Recently, representation learning with contrastive learning algorithms has been successfully applied to challenging unlabeled datasets. However, these methods are unable to distinguish important features from unimportant ones under simply unsupervise
Externí odkaz:
http://arxiv.org/abs/2408.04891
Autor:
Ren, Pu, Nakata, Rie, Lacour, Maxime, Naiman, Ilan, Nakata, Nori, Song, Jialin, Bi, Zhengfa, Malik, Osman Asif, Morozov, Dmitriy, Azencot, Omri, Erichson, N. Benjamin, Mahoney, Michael W.
Predicting high-fidelity ground motions for future earthquakes is crucial for seismic hazard assessment and infrastructure resilience. Conventional empirical simulations suffer from sparse sensor distribution and geographically localized earthquake l
Externí odkaz:
http://arxiv.org/abs/2407.15089
Autor:
Lyu, Dongwei, Nakata, Rie, Ren, Pu, Mahoney, Michael W., Pitarka, Arben, Nakata, Nori, Erichson, N. Benjamin
Large earthquakes can be destructive and quickly wreak havoc on a landscape. To mitigate immediate threats, early warning systems have been developed to alert residents, emergency responders, and critical infrastructure operators seconds to a minute
Externí odkaz:
http://arxiv.org/abs/2405.20516
Autor:
Nakata, Wataru, Seki, Kentaro, Yanaka, Hitomi, Saito, Yuki, Takamichi, Shinnosuke, Saruwatari, Hiroshi
Spoken dialogue plays a crucial role in human-AI interactions, necessitating dialogue-oriented spoken language models (SLMs). To develop versatile SLMs, large-scale and diverse speech datasets are essential. Additionally, to ensure hiqh-quality speec
Externí odkaz:
http://arxiv.org/abs/2407.15828
Autor:
Lashner, Jack, Zheng, Kaiwen, Crowley, Kevin T., Galitzki, Nicholas, Harrington, Kathleen, Nakata, Hironobu, Silva-Feaver, Max
The Simons Observatory (SO) is a ground-based cosmic microwave background experiment currently being deployed to Cerro Toco in the Atacama Desert of Chile. The initial deployment of SO, consisting of three 0.46m-diameter small-aperture telescopes and
Externí odkaz:
http://arxiv.org/abs/2407.14615
Autor:
Yatomi, Go, Nakata, Motoki
A novel information entropy of turbulence systems with multiple field quantities is formulated. Inspired by quantum mechanics, the von Neumann entropy (vNE) and the entanglement entropy(EE) are derived from a density matrix for the turbulence state i
Externí odkaz:
http://arxiv.org/abs/2407.09098