Rchr
J-GLOBAL ID:202001010582322262   Update date: Nov. 22, 2022

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 (19):
  • 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
  • Bowen Wang, Liangzhi Li, Manisha Verma, Yuta Nakashima, Ryo Kawasaki, Hajime Nagahara. Match them up: visually explainable few-shot image classification. Applied Intelligence. 2022
  • Bowen Wang, Liangzhi Li, Yuta Nakashima, Takehiro Yamamoto, Hiroaki Ohshima, Yoshiyuki Shoji, Kenro Aihara, Noriko Kando. Image Retrieval by Hierarchy-aware Deep Hashing Based on Multi-task Learning. Proceedings of the 2021 International Conference on Multimedia Retrieval. 2021
  • Bowen Wang, Liangzhi Li, Manisha Verma, Yuta Nakashima, Ryo Kawasaki, Hajime Nagahara. MTUNet: Few-Shot Image Classification With Visual Explanations. IEEE Conference on Computer Vision and Pattern Recognition Workshops. 2021. 2294-2298
  • Bowen Wang, Liangzhi Li, Yuta Nakashima, Ryo Kawasaki, Hajime Nagahara, Yasushi Yagi. Noisy-LSTM: Improving Temporal Awareness for Video Semantic Segmentation. IEEE Access. 2021. 9. 46810-46820
more...
MISC (2):
  • 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
  • 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)
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