Masahiro Hashimoto

According to our database1, Masahiro Hashimoto authored at least 22 papers between 1970 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Awards

IEEE Fellow

IEEE Fellow 1998, "For contributions to electromagnetic theory, especially for guided-wave optics.".

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2023
Attention induction for a CT volume classification of COVID-19.
Int. J. Comput. Assist. Radiol. Surg., February, 2023

Identifying Suspicious Regions of Covid-19 by Abnormality-Sensitive Activation Mapping.
CoRR, 2023

Improved method for COVID-19 classification of complex-architecture CNN from chest CT volumes using orthogonal ensemble networks.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, 2023

Classification of COVID-19 cases from chest CT volumes using hybrid model of 3D CNN and 3D MLP-mixer.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, 2023

2022
Automated classification method of COVID-19 cases from chest CT volumes using 2D and 3D hybrid CNN for anisotropic volumes.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022

2021
Unsupervised segmentation of COVID-19 infected lung clinical CT volumes using image inpainting and representation learning.
Proceedings of the Medical Imaging 2021: Image Processing, Online, February 15-19, 2021, 2021

Lung infection and normal region segmentation from CT volumes of COVID-19 cases.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

Extremely imbalanced subarachnoid hemorrhage detection based on DenseNet-LSTM network with class-balanced loss and transfer learning.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

Extraction of lung and lesion regions from COVID-19 CT volumes using 3D fully convolutional networks.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

COVID-19 Infection Segmentation from Chest CT Images Based on Scale Uncertainty.
Proceedings of the Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning, 2021

2020
Usefulness of fine-tuning for deep learning based multi-organ regions segmentation method from non-contrast CT volumes using small training dataset.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

Low-Information-Loss Anonymization of Trajectory Data Considering Map Information.
Proceedings of the 29th IEEE International Symposium on Industrial Electronics, 2020

Anomaly Detection Based on Histogram Methodology and Factor Analysis Using LightGBM for Cooling Systems.
Proceedings of the 25th IEEE International Conference on Emerging Technologies and Factory Automation, 2020

2019
Semantic Segmentation of Thigh Muscle using 2.5D Deep Learning Network Trained with Limited Datasets.
CoRR, 2019

2010
"The Center of Scattering"-Where is the Center of a Polygonal Cylinder for Electromagnetic Scattering ?-.
IEICE Trans. Electron., 2010

2009
Some Remarks on the Extension of Numerical Data to the Complex Space for Radiation Patterns in Electromagnetic Scattering Problems.
IEICE Trans. Electron., 2009

2008
An improved Internet-based melanoma screening system with dermatologist-like tumor area extraction algorithm.
Comput. Medical Imaging Graph., 2008

2005
An Internet-based Melanoma Diagnostic System - Toward the Practical Application.
Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2005

1995
An object extraction method using sampled active contour model.
Syst. Comput. Jpn., 1995

1994
Limitations of lip-reading advantage by desynchronizing visual and auditory information in speech.
Proceedings of the 3rd International Conference on Spoken Language Processing, 1994

1991
Basic Concepts of Timing-oriented Design Automation for High-performance Mainframe Computers.
Proceedings of the 28th Design Automation Conference, 1991

1970
A Method for Solving Large Matrix Equations Reduced From Fredholm Integral Equations of the Second Kind.
J. ACM, 1970


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