Zobrazeno 1 - 10
of 197
pro vyhledávání: '"TOMOYA SAKAI"'
Autor:
Takeru SATO, Tsunehisa SUZUKI, Tatsuya FUJII, Mitsuyoshi NOMURA, Hiroshi SAITO, Takashi YAMAKAWA, Yuki SHISHIKURA, Tomoya SAKAI
Publikováno v:
Nihon Kikai Gakkai ronbunshu, Vol 89, Iss 928, Pp 23-00161-23-00161 (2023)
The purpose of this paper is to examine which coating material on tool edges is best for cutting spheroidal graphite cast iron containing 35% Nickel (Ni) and to understand the relation between friction properties of the coatings and cutting ability.
Externí odkaz:
https://doaj.org/article/5fdbfe353c544f5898a8b58f89569a63
Autor:
Eiji Mitate, Kirin Inoue, Retsushi Sato, Youichi Shimomoto, Seigo Ohba, Kinuko Ogata, Tomoya Sakai, Jun Ohno, Ikuo Yamamoto, Izumi Asahina
Publikováno v:
Diagnostic Pathology, Vol 17, Iss 1, Pp 1-8 (2022)
Abstract Background We aimed to develop an artificial intelligence (AI)-assisted oral cytology method, similar to cervical cytology. We focused on the detection of cell nuclei because the ratio of cell nuclei to cytoplasm increases with increasing ce
Externí odkaz:
https://doaj.org/article/39c8bbcac1ab44aa907c2a55ea7544b3
Autor:
Toshikazu Fukumitsu, Yasushi Obase, Yuji Ishimatsu, Shota Nakashima, Hiroshi Ishimoto, Noriho Sakamoto, Kosei Nishitsuji, Shunpei Shiwa, Tomoya Sakai, Sueharu Miyahara, Kazuto Ashizawa, Hiroshi Mukae, Ryo Kozu
Publikováno v:
BMC Pulmonary Medicine, Vol 19, Iss 1, Pp 1-8 (2019)
Abstract Background Honeycombing on high-resolution computed tomography (HRCT) is a distinguishing feature of usual interstitial pneumonia and predictive of poor outcome in interstitial lung diseases (ILDs). Although fine crackles are common in ILD p
Externí odkaz:
https://doaj.org/article/78d38b15cf594c8cb6d81ffb2db7ec58
Publikováno v:
2022 International Conference on Digital Image Computing: Techniques and Applications (DICTA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6cc236dfcfe9e981019d2c6f845c7387
https://doi.org/10.1109/dicta56598.2022.10034581
https://doi.org/10.1109/dicta56598.2022.10034581
Autor:
Tomoya Sakai
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6458c96164cfde01e134083002ab56e1
https://doi.org/10.1145/3534678.3539465
https://doi.org/10.1145/3534678.3539465
Publikováno v:
Medicine; 7/7/2023, Vol. 102 Issue 27, p1-4, 4p
Autor:
Tomoya Sakai, Nobuyuki Shimizu
Publikováno v:
AAAI
The goal of binary classification is to identify whether an input sample belongs to positive or negative classes. Usually, supervised learning is applied to obtain a classification rule, but in real-world applications, it is conceivable that only pos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::149bbbc61b6bd40aff106ff78e806ff2
https://doi.org/10.1609/aaai.v33i01.33014838
https://doi.org/10.1609/aaai.v33i01.33014838
Autor:
Tomoya Sakai, Naoto Ohsaka
Publikováno v:
Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) ISBN: 9781611976700
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e91ea8609ce3920e6864672d50316cc5
https://doi.org/10.1137/1.9781611976700.42
https://doi.org/10.1137/1.9781611976700.42
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783030757649
PAKDD (2)
PAKDD (2)
With set-wise (exact-k, slate, combinatorial) recommendation, we aim to optimize the whole set of items to recommend while taking the dependency among items into consideration. This enables us to model, for example, the substitution relationship of i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::51c57fa362f817df0cf836600c47f389
https://doi.org/10.1007/978-3-030-75765-6_40
https://doi.org/10.1007/978-3-030-75765-6_40
Autor:
Tomoya Sakai
Publikováno v:
Machine Learning and Knowledge Discovery in Databases. Research Track ISBN: 9783030864859
ECML/PKDD (1)
ECML/PKDD (1)
Making predictions in target unseen domains without training samples is frequent in real-world applications, such as new products’ sales predictions. Zero-shot domain adaptation (ZSDA) has been studied to achieve this important but difficult task.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2ebae02a5b075f307f2caf3a0b7ebfb
https://doi.org/10.1007/978-3-030-86486-6_35
https://doi.org/10.1007/978-3-030-86486-6_35