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Ryosuke Takayama
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2020 – today
- 2023
- [c6]Ryosuke Takayama, Masanao Natsumeda, Takehisa Yairi:
A semi-supervised RUL prediction with likelihood-based pseudo labeling for suspension histories. ICPHM 2023: 296-303 - 2022
- [c5]Ryosuke Takayama, Takehisa Yairi, Nana Tamai:
Nonstationary and Sparse Linear Regression for State Prediction of Artificial Systems. SICE 2022: 553-558
2010 – 2019
- 2018
- [c4]Xiangrong Zhou, Kazuma Yamada, Takuya Kojima, Ryosuke Takayama, Song Wang
, Xinxin Zhou, Takeshi Hara, Hiroshi Fujita:
Performance evaluation of 2D and 3D deep learning approaches for automatic segmentation of multiple organs on CT images. Medical Imaging: Computer-Aided Diagnosis 2018: 105752C - 2017
- [c3]Xiangrong Zhou, Ryosuke Takayama, Song Wang
, Xinxin Zhou, Takeshi Hara, Hiroshi Fujita:
Automated segmentation of 3D anatomical structures on CT images by using a deep convolutional network based on end-to-end learning approach. Medical Imaging: Image Processing 2017: 1013324 - 2016
- [c2]Xiangrong Zhou, Takaaki Ito, Ryosuke Takayama, Song Wang
, Takeshi Hara, Hiroshi Fujita:
Three-Dimensional CT Image Segmentation by Combining 2D Fully Convolutional Network with 3D Majority Voting. LABELS/DLMIA@MICCAI 2016: 111-120 - 2014
- [c1]Ryosuke Takayama, Shuichi Arai:
Fast multiresolution Gabor Transform based on synthesis of high frequency resolution spectrum from low frequency resolution spectra. GlobalSIP 2014: 694-697
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