Hiroshi Murata

发表

Module packing based on the BSG-structure and IC layout applications

Yoji Kajitani, Shigetoshi Nakatake, Kunihiro Fujiyoshi, 1998, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

Wired and Wireless Network Convergence in 5G/IoT Era

Daniel C. Kilper, Hideki Tode, Atsushi Kanno, 2019, 2019 24th OptoElectronics and Communications Conference (OECC) and 2019 International Conference on Photonics in Switching and Computing (PSC).

Novel electro-optic microwave-lightwave converters utilizing a patch antenna embedded with a narrow gap

Yasuyuki Okamura, Yusuf Nur Wijayanto, Hiroshi Murata, 2011, IEICE Electron. Express.

Antenna-Coupled Electrode Electro-Optic Modulator and 28 GHz-Band Wireless Signal Transfer over Fiber for 5G Mobile Systems

Satoru Kurokawa, Yoshikazu Toba, Masahiro Sato, 2019, 2019 24th OptoElectronics and Communications Conference (OECC) and 2019 International Conference on Photonics in Switching and Computing (PSC).

An algorithm to enumerate all floorplans by using Q-sequence and its applications to the boundary constraint problam

Atsushi Takahashi, Liyan Jin, Keishi Sakanushi, 2001 .

D321 Report on Beam Steerable Directive Antennas

Naruto Yonemoto, Matthias Steeg, Andreas Stohr, 2018 .

Array-antenna-electrode electro-optic modulator for millimeter-wireless communication systems

Yasuyuki Okamura, Toshiyuki Inoue, Hidehisa Shiomi, 2016, 2016 IEEE Sixth International Conference on Communications and Electronics (ICCE).

Radio technologies for 5G using Advanced Photonic Infrastructure for Dense user environments - D321 Report on Beam Steerable Directive Antennas

Nathan J. Gomes, Toshiyuki Inoue, Naruto Yonemoto, 2018 .

A Joint Multitask Learning Model for Cross-sectional and Longitudinal Predictions of Visual Field Using OCT

Kenji Yamanishi, Taichi Kiwaki, Kazuhiko Mori, 2021, Ophthalmology science.

PAMI: A Computational Module for Joint Estimation and Progression Prediction of Glaucoma

Kenji Yamanishi, Taichi Kiwaki, Ryo Asaoka, 2021, KDD.

How Many Visual Fields Are Required to Precisely Predict Future Test Results in Glaucoma Patients When Using Different Trend Analyses?

Ryo Asaoka, Chihiro Mayama, Yuri Fujino, 2015, Investigative ophthalmology & visual science.

Discriminating between Glaucoma and Normal Eyes Using Optical Coherence Tomography and the ‘Random Forests’ Classifier

Ryo Asaoka, Makoto Araie, Hiroyo Hirasawa, 2014, PloS one.

Effects of Study Population, Labeling and Training on Glaucoma Detection Using Deep Learning Algorithms

Christopher Bowd, Linda M. Zangwill, Robert N. Weinreb, 2020, Translational vision science & technology.

Cross-sectional study: Does combining optical coherence tomography measurements using the ‘Random Forest’ decision tree classifier improve the prediction of the presence of perimetric deterioration in glaucoma suspects?

Makoto Aihara, Koichiro Sugimoto, Ryo Asaoka, 2013, BMJ Open.

Validation of a Deep Learning Model to Screen for Glaucoma Using Images from Different Fundus Cameras and Data Augmentation.

Yoshiaki Kiuchi, Ryo Asaoka, Yuri Fujino, 2019, Ophthalmology. Glaucoma.

The association between photoreceptor layer thickness measured by optical coherence tomography and visual sensitivity in glaucomatous eyes

Kenji Inoue, Ryo Asaoka, Mieko Yanagisawa, 2017, PloS one.

Evaluation of various machine learning methods to predict vision-related quality of life from visual field data and visual acuity in patients with glaucoma

Ryo Asaoka, Makoto Araie, Hiroyo Hirasawa, 2014, British Journal of Ophthalmology.

Validating Variational Bayes Linear Regression Method With Multi-Central Datasets

Linda M. Zangwill, Kenji Kashiwagi, Katsuyoshi Suzuki, 2018, Investigative ophthalmology & visual science.

Mapping the Central 10° Visual Field to the Optic Nerve Head Using the Structure-Function Relationship.

Kenji Inoue, Ryo Asaoka, Mieko Yanagisawa, 2018, Investigative ophthalmology & visual science.

Identifying "preperimetric" glaucoma in standard automated perimetry visual fields.

Ryo Asaoka, Makoto Araie, Kazunori Hirasawa, 2014, Investigative ophthalmology & visual science.

Applying "Lasso" Regression to Predict Future Visual Field Progression in Glaucoma Patients.

Ryo Asaoka, Chihiro Mayama, Yuri Fujino, 2015, Investigative ophthalmology & visual science.

Clustering visual field test points based on rates of progression to improve the prediction of future damage.

Ryo Asaoka, Hiroyo Hirasawa, Chihiro Mayama, 2014, Investigative ophthalmology & visual science.

A new approach to measure visual field progression in glaucoma patients using variational bayes linear regression.

Ryo Asaoka, Makoto Araie, Hiroshi Murata, 2014, Investigative ophthalmology & visual science.

Differences in Relationship Between Macular Inner Retinal Layer Thickness and Retinal Sensitivity in Eyes With Early and Progressed Glaucoma.

Masanori Hangai, Nagahisa Yoshimura, Makoto Araie, 2016, Investigative ophthalmology & visual science.

Imaging mouse retinal ganglion cells and their loss in vivo by a fundus camera in the normal and ischemia-reperfusion model.

Makoto Aihara, Makoto Araie, Hiroshi Murata, 2008, Investigative ophthalmology & visual science.

Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning.

Siamak Yousefi, Kenji Yamanishi, Taichi Kiwaki, 2018, American journal of ophthalmology.

Detection of Progression of Glaucomatous Visual Field Damage Using the Point-Wise Method with the Binomial Test

Ryo Asaoka, Hiroyo Hirasawa, Chihiro Mayama, 2013, PloS one.