Ryosuke Takayama - researchr alias

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Viewing Publication 1 - 6 from 6

2023

A semi-supervised RUL prediction with likelihood-based pseudo labeling for suspension historiesRyosuke Takayama, Masanao Natsumeda, Takehisa Yairi. icphm 2023: 296-303 [doi]

2022

Nonstationary and Sparse Linear Regression for State Prediction of Artificial SystemsRyosuke Takayama, Takehisa Yairi, Nana Tamai. sice 2022: 553-558 [doi]

2018

Performance evaluation of 2D and 3D deep learning approaches for automatic segmentation of multiple organs on CT imagesXiangrong Zhou, Kazuma Yamada, Takuya Kojima, Ryosuke Takayama, Song Wang, Xinxin Zhou, Takeshi Hara, Hiroshi Fujita 0001. micad 2018: [doi]

2017

Automated segmentation of 3D anatomical structures on CT images by using a deep convolutional network based on end-to-end learning approachXiangrong Zhou, Ryosuke Takayama, Song Wang, Xinxin Zhou, Takeshi Hara, Hiroshi Fujita 0001. miip 2017: 1013324 [doi]

2016

Three-Dimensional CT Image Segmentation by Combining 2D Fully Convolutional Network with 3D Majority VotingXiangrong Zhou, Takaaki Ito, Ryosuke Takayama, Song Wang, Takeshi Hara, Hiroshi Fujita 0001. miccai 2016: 111-120 [doi]

2014

Fast multiresolution Gabor Transform based on synthesis of high frequency resolution spectrum from low frequency resolution spectraRyosuke Takayama, Shuichi Arai. globalsip 2014: 694-697 [doi]

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