Zobrazeno 1 - 10
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pro vyhledávání: '"ABE, Hiroyuki"'
We discuss the behavior of the one-loop vacuum energy of 10 dimensional (10D) super Yang-Mills theory on magnetized tori $\mathbb{R}^{1,3}\times (\mathbb{T}^2)^3$ in the presence of the Abelian magnetic fluxes, including all the contributions from Ka
Externí odkaz:
http://arxiv.org/abs/2402.09767
Autor:
Liu, Xiaoqing, Araki, Kengo, Harada, Shota, Yoshizawa, Akihiko, Terada, Kazuhiro, Kurata, Mariyo, Nakajima, Naoki, Abe, Hiroyuki, Ushiku, Tetsuo, Bise, Ryoma
The domain shift in pathological segmentation is an important problem, where a network trained by a source domain (collected at a specific hospital) does not work well in the target domain (from different hospitals) due to the different image feature
Externí odkaz:
http://arxiv.org/abs/2304.13513
Autor:
Takahama, Shusuke, Kurose, Yusuke, Mukuta, Yusuke, Abe, Hiroyuki, Yoshizawa, Akihiko, Ushiku, Tetsuo, Fukayama, Masashi, Kitagawa, Masanobu, Kitsuregawa, Masaru, Harada, Tatsuya
Pathological image analysis is an important process for detecting abnormalities such as cancer from cell images. However, since the image size is generally very large, the cost of providing detailed annotations is high, which makes it difficult to ap
Externí odkaz:
http://arxiv.org/abs/2304.03537
Autor:
Harada, Shota, Bise, Ryoma, Araki, Kengo, Yoshizawa, Akihiko, Terada, Kazuhiro, Kurata, Mariyo, Nakajima, Naoki, Abe, Hiroyuki, Ushiku, Tetsuo, Uchida, Seiichi
Semi-supervised domain adaptation is a technique to build a classifier for a target domain by modifying a classifier in another (source) domain using many unlabeled samples and a small number of labeled samples from the target domain. In this paper,
Externí odkaz:
http://arxiv.org/abs/2303.01283
Autor:
Bogdanova, Anna, Imakura, Akira, Sakurai, Tetsuya, Fujii, Tomoya, Sakamoto, Teppei, Abe, Hiroyuki
Transparency of Machine Learning models used for decision support in various industries becomes essential for ensuring their ethical use. To that end, feature attribution methods such as SHAP (SHapley Additive exPlanations) are widely used to explain
Externí odkaz:
http://arxiv.org/abs/2212.03373
Autor:
Imakura, Akira, Sakurai, Tetsuya, Okada, Yukihiko, Fujii, Tomoya, Sakamoto, Teppei, Abe, Hiroyuki
Multi-source data fusion, in which multiple data sources are jointly analyzed to obtain improved information, has considerable research attention. For the datasets of multiple medical institutions, data confidentiality and cross-institutional communi
Externí odkaz:
http://arxiv.org/abs/2208.14611
Autor:
Abe, Hiroyuki1,2 (AUTHOR), Mori, Kentaro1 (AUTHOR), Fukui, Issei1 (AUTHOR), Tamase, Akira1 (AUTHOR), Yamashita, Ryotaro3 (AUTHOR), Takeda, Mutsuki3 (AUTHOR), Nakano, Tatsu3 (AUTHOR), Nomura, Motohiro1 (AUTHOR) nomura413jp@yahoo.co.jp, Yamamoto, Tetsuya2 (AUTHOR)
Publikováno v:
Asian Journal of Neurosurgery. Jun2024, Vol. 19 Issue 2, p174-178. 5p.
Externí odkaz:
http://hdl.handle.net/2237/9094
Autor:
Usui, Genki, Matsusaka, Keisuke, Huang, Kie Kyon, Zhu, Feng, Shinozaki, Tomohiro, Fukuyo, Masaki, Rahmutulla, Bahityar, Yogi, Norikazu, Okada, Tomoka, Minami, Mizuki, Seki, Motoaki, Sakai, Eiji, Fujibayashi, Kazutoshi, Kwok Tsao, Stephen Kin, Khor, Christopher, Ang, Tiing Leong, Abe, Hiroyuki, Matsubara, Hisahiro, Fukayama, Masashi, Gunji, Toshiaki, Matsuhashi, Nobuyuki, Morikawa, Teppei, Ushiku, Tetsuo, Yeoh, Khay Guan, Tan, Patrick, Kaneda, Atsushi
Publikováno v:
In eBioMedicine December 2023 98
Autor:
Ren, Zhen, Pineda, Federico D., Howard, Frederick M., Fan, Xiaobing, Nanda, Rita, Abe, Hiroyuki, Kulkarni, Kirti, Karczmar, Gregory S.
Publikováno v:
In Magnetic Resonance Imaging December 2023 104:9-15