Zobrazeno 1 - 10
of 707
pro vyhledávání: '"Hayashi Kazuki"'
Autor:
Migliari Matteo, Hayashi Kazuki, Ulanowski Yan, Laporte Stéphane, Hendel Martin, Parison Sophie, Despax Julien, Chesne Loïc, Baverel Olivier
Publikováno v:
SHS Web of Conferences, Vol 198, p 02004 (2024)
Le changement climatique exige une remise en question des pratiques d’urbanisation. Les environnements urbains influencent la relation des résidents avec les espaces extérieurs et intérieurs, avec des conséquences sur la consommation d’énerg
Externí odkaz:
https://doaj.org/article/9018b888c926442a8c37625b481ced4d
This study proposes a methodology to utilize machine learning (ML) for topology optimization of periodic lattice structures. In particular, we investigate data representation of lattice structures used as input data for ML models to improve the perfo
Externí odkaz:
http://arxiv.org/abs/2411.13869
Autor:
Ozaki, Shintaro, Hayashi, Kazuki, Oba, Miyu, Sakai, Yusuke, Kamigaito, Hidetaka, Watanabe, Taro
A large part of human communication relies on nonverbal cues such as facial expressions, eye contact, and body language. Unlike language or sign language, such nonverbal communication lacks formal rules, requiring complex reasoning based on commonsen
Externí odkaz:
http://arxiv.org/abs/2410.13206
Autor:
Ozaki, Shintaro, Hayashi, Kazuki, Sakai, Yusuke, Kamigaito, Hidetaka, Hayashi, Katsuhiko, Watanabe, Taro
As the performance of Large-scale Vision Language Models (LVLMs) improves, they are increasingly capable of responding in multiple languages, and there is an expectation that the demand for explanations generated by LVLMs will grow. However, pre-trai
Externí odkaz:
http://arxiv.org/abs/2409.01584
Large-scale vision-language models (LVLMs) output text from images and instructions, demonstrating advanced capabilities in text generation and comprehension. However, it has not been clarified to what extent LVLMs understand the knowledge necessary
Externí odkaz:
http://arxiv.org/abs/2403.00068
Autor:
Saito, Shigeki, Hayashi, Kazuki, Ide, Yusuke, Sakai, Yusuke, Onishi, Kazuma, Suzuki, Toma, Gobara, Seiji, Kamigaito, Hidetaka, Hayashi, Katsuhiko, Watanabe, Taro
Large-scale vision language models (LVLMs) are language models that are capable of processing images and text inputs by a single model. This paper explores the use of LVLMs to generate review texts for images. The ability of LVLMs to review images is
Externí odkaz:
http://arxiv.org/abs/2402.12121
A multiobjective optimization method is proposed for obtaining the optimal plane trusses simultaneously for various aspect ratios of the initial ground structure as a set of Pareto optimal solutions generated through a single optimization process. Th
Externí odkaz:
http://arxiv.org/abs/2307.16473
Autor:
Kamata, Makoto, Hayashi, Kazuki, Watanabe, Noriyuki, Nakazawa, Kazuhiro, Tsuru, Takeshi, Akizuki, Yuki, Nagano, Hosei
Publikováno v:
In International Journal of Heat and Mass Transfer January 2025 236 Part 2
Recently, motion generation by machine learning has been actively researched to automate various tasks. Imitation learning is one such method that learns motions from data collected in advance. However, executing long-term tasks remains challenging.
Externí odkaz:
http://arxiv.org/abs/2203.08619
Publikováno v:
2021 IEEE International Conference on Mechatronics (ICM), Pages 1-7, 2021
In the near future, robots are expected to work with humans or operate alone and may replace human workers in various fields such as homes and factories. In a previous study, we proposed bilateral control-based imitation learning that enables robots
Externí odkaz:
http://arxiv.org/abs/2103.08879