6 citations · 9 across the 5 of their papers we have counts for
5 papers
Aging prediction using deep generative model toward the development of preventive medicine
Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura +2
From birth to death, we all experience surprisingly ubiquitous changes over time due to aging. If we can predict aging in the digital domain, that is, the digital twin of the human…
X2CT-FLOW: Maximum a posteriori reconstruction using a progressive flow-based deep generative model for ultra sparse-view computed tomography in ultra low-dose protocols
Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura +4
Ultra sparse-view computed tomography (CT) algorithms can reduce radiation exposure of patients, but those algorithms lack an explicit cycle consistency loss minimization and an ex…
KART: Parameterization of Privacy Leakage Scenarios from Pre-trained Language Models
Yuta Nakamura, Shouhei Hanaoka, Yukihiro Nomura +5
For the safe sharing pre-trained language models, no guidelines exist at present owing to the difficulty in estimating the upper bound of the risk of privacy leakage. One problem i…
On the Matrix-Free Generation of Adversarial Perturbations for Black-Box Attacks
Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura +2
In general, adversarial perturbations superimposed on inputs are realistic threats for a deep neural network (DNN). In this paper, we propose a practical generation method of such…
A versatile anomaly detection method for medical images with a flow-based generative model in semi-supervision setting
H. Shibata, S. Hanaoka, Y. Nomura +5
Oversight in medical images is a crucial problem, and timely reporting of medical images is desired. Therefore, an all-purpose anomaly detection method that can detect virtually al…