Rchr
J-GLOBAL ID：202001010582322262
Update date: Mar. 30, 2024
LI LIANGZHI
リ リョウチ | LI LIANGZHI
Affiliation and department：
Job title：
Specially Appointed Assistant Professor
Homepage URL (1)：
https://www.liangzhili.com
Research theme for competitive and other funds (3)：
- 2022 - 2026 Risk profiling for cardiovascular diseases using the retinal images
- 2021 - 2023 Explainable Artificial Intelligence for Medical Applications
- 2020 - 2022 Removing the Burden of Data Labeling: Automatic Surgical Video Understanding with Unsupervised Learning
Papers (23)：
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Bowen Wang, Jiaxin Zhang, Ran Zhang, Yunqin Li, Liangzhi Li, Yuta Nakashima. Improving facade parsing with vision transformers and line integration. Advanced Engineering Informatics. 2024. 60. 102463-102463
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Bowen Wang, Liangzhi Li, Yuta Nakashima, Ryo Kawasaki, Hajime Nagahara. Real-time estimation of the remaining surgery duration for cataract surgery using deep convolutional neural networks and long short-term memory. BMC Medical Informatics and Decision Making. 2023. 23. 1
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Liangzhi Li, Manisha Verma, Bowen Wang, Yuta Nakashima, Hajime Nagahara, Ryo Kawasaki. Automated grading system of retinal arterio-venous crossing patterns: A deep learning approach replicating ophthalmologist’s diagnostic process of arteriolosclerosis. PLOS Digital Health. 2023. 2. 1
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Hong Tang, Xiangzheng Ling, Liangzhi Li, Liyan Xiong, Yu Yao, Xiaohui Huang. One-shot pruning of gated recurrent unit neural network by sensitivity for time-series prediction. Neurocomputing. 2022. 512. 15-24
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Bowen Wang, Liangzhi Li, Manisha Verma, Yuta Nakashima, Ryo Kawasaki, Hajime Nagahara. Match them up: visually explainable few-shot image classification. Applied Intelligence. 2022
ｍore...
MISC (2)：
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Ryo Kawasaki, Yiming Qian, Liangzhi Li, Kohji Nishida, Yuta Nakashima, Hajime Nagahara. Cardiovascular Disease Risk Prediction using Retinal Images via Explainable-AI based models with Traditional CVD risk factor estimation. INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE. 2022. 63. 7
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Kawasaki, Ryo, Li, Liangzhi, Nakashima, Yuta, Nagahara, Hajime, Ohkubo, Takayoshi, Nishida, Kohji. A fully automated grading system for the retinal arteriovenous crossing signs using deep neural network. Investigative Ophthalmology & Visual Science. 2020. 61. 7. 1930-1930
Awards (5)：
- 2019/03 - Muroran Institute of Technology Rangaku Award
- 2018/12 - IEEE Sapporo Section Best Paper Award Eyes in the Dark: Distributed Scene Understanding for Disaster Management
- 2018/10 - Dr. Sato Noriyasu Memorial Scholarship Award for International Activities
- 2017/12 - IEEE Communications Letters Exemplary Reviewer
- 2017/06 - International Conference on Frontier of Computer Science and Technology (FCST) Best Paper Award Everything is Image: CNN-based Short-term Electrical Load Forecasting for Smart Grid
Association Membership(s) (1)：
Institute of Electrical and Electronics Engineers (IEEE)
