Zobrazeno 1 - 10
of 1 443
pro vyhledávání: '"Takahiro, Ogawa"'
Autor:
Chao, Denny, Komatsu, Keiji, Matsuura, Takanori, Cheng, James, Stavrou, Stella C., Jayanetti, Jay, Ting-Ling Chang, Takahiro Ogawa
Publikováno v:
International Journal of Oral & Maxillofacial Implants; Jul/Aug2024, Vol. 39 Issue 4, p603-614, 12p
Publikováno v:
IEEE Access, Vol 12, Pp 127244-127258 (2024)
This paper presents a multi-modal Gaussian process latent variable model with semi-supervised label dequantization. In real-world applications, although user ratings are often attached to the content, they are roughly provided and are limited in numb
Externí odkaz:
https://doaj.org/article/0e6ad5558f8341caafa99dc3c55fcb30
Publikováno v:
IEEE Access, Vol 12, Pp 23626-23635 (2024)
The primary objective of a recommender system (RS) is to enhance user satisfaction, which serves as the gold standard for evaluation. In order to support the advancement of RS, it is crucial to study how to accurately measure user satisfaction. This
Externí odkaz:
https://doaj.org/article/721dd2228a8f4416a12ef7e2c17e5edc
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 5, Pp 150-159 (2024)
Although text-guided image manipulation approaches have demonstrated highly accurate performance for editing the appearance of images in a virtual or simple scenario, their real-world applications face significant challenges. The primary cause of the
Externí odkaz:
https://doaj.org/article/06c8c4517dec4bf191a4744448f0e48d
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 5, Pp 177-185 (2024)
There are various sentiment theories for categorizing human sentiments into several discrete sentiment categories, which means that the theory used for training sentiment prediction methods does not always match that used in the test phase. As a solu
Externí odkaz:
https://doaj.org/article/a1078785b1784e41a4a4814c5a216e18
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 5, Pp 92-100 (2024)
This article proposes a method for transferring knowledge of semantic segmentation from a labeled source domain to an unlabeled target domain without using the source-domain data. Such a problem is called source-data-free domain adaptation, in which
Externí odkaz:
https://doaj.org/article/f0b5b6486b8f4abd99cfd6d8d95c7344
Publikováno v:
Applied Sciences, Vol 14, Iss 11, p 4847 (2024)
Sports data analysis has significantly advanced and become an indispensable technology for planning strategy and enhancing competitiveness. In soccer, shot prediction has been realized on the basis of historical match situations, and its results cont
Externí odkaz:
https://doaj.org/article/e2cc831317b84f7ea8e132307ce2ab7b
Autor:
Tatsuya Umemoto, Masanori Hasegawa, Soichiro Yuzuriha, Tatsuo Kano, Takahiro Ogawa, Masayoshi Kawakami, Mayura Nakano, Hakushi Kim, Masahiro Nitta, Yoshiaki Kawamura, Sunao Shoji, Ryuichi Mizuno, Akira Miyajima
Publikováno v:
BMC Urology, Vol 23, Iss 1, Pp 1-8 (2023)
Abstract Background Collecting system entry in robot-assisted partial nephrectomy may occur even in cases showing a low N factor in the R.E.N.A.L nephrometry score. Therefore, in this study, we focused on the tumor contact surface area with the adjac
Externí odkaz:
https://doaj.org/article/419330253316450ea638297215d4657c
Autor:
Keisuke Maeda, Takahiro Ogawa, Tasuku Kayama, Takuya Sasaki, Kazuki Tainaka, Masaaki Murakami, Miki Haseyama
Publikováno v:
Bioengineering, Vol 11, Iss 6, p 523 (2024)
This study presents a trial analysis that uses brain activity information obtained from mice to detect rheumatoid arthritis (RA) in its presymptomatic stages. Specifically, we confirmed that F759 mice, serving as a mouse model of RA that is dependent
Externí odkaz:
https://doaj.org/article/7ceaf2aa807a41b099ac733675afa7bd
Publikováno v:
Sensors, Vol 24, Iss 11, p 3440 (2024)
This paper proposes a multimodal Transformer model that uses time-series data to detect and predict winter road surface conditions. For detecting or predicting road surface conditions, the previous approach focuses on the cooperative use of multiple
Externí odkaz:
https://doaj.org/article/2503dc886dbf41cf8b49ce3d9ab905f9