LIANGZHI LI

Profile Information

Affiliation: Specially Appointed Assistant Professor, Institute for Datability Science, Osaka University

Researcher number: 10875545
ORCID ID: https://orcid.org/0000-0002-8879-5957
J-GLOBAL ID: 202001010582322262
researchmap Member ID: R000002997

External link: https://www.liangzhili.com

Awards

Mar, 2019

Rangaku Award, Muroran Institute of Technology
Dec, 2018

IEEE Sapporo Section Best Paper Award, Eyes in the Dark: Distributed Scene Understanding for Disaster Management
Oct, 2018

Dr. Sato Noriyasu Memorial Scholarship Award for International Activities
Dec, 2017

IEEE Communications Letters Exemplary Reviewer
Jun, 2017

Best Paper Award, Everything is Image: CNN-based Short-term Electrical Load Forecasting for Smart Grid, International Conference on Frontier of Computer Science and Technology (FCST)

Papers

One-shot pruning of gated recurrent unit neural network by sensitivity for time-series prediction

Hong Tang, Xiangzheng Ling, Liangzhi Li, Liyan Xiong, Yu Yao, Xiaohui Huang

Neurocomputing, 512 15-24, Nov 1, 2022 Peer-reviewed
Match them up: visually explainable few-shot image classification

Bowen Wang, Liangzhi Li, Manisha Verma, Yuta Nakashima, Ryo Kawasaki, Hajime Nagahara

Applied Intelligence, 2022 Peer-reviewed
Image Retrieval by Hierarchy-aware Deep Hashing Based on Multi-task Learning

Bowen Wang, Liangzhi Li, Yuta Nakashima, Takehiro Yamamoto, Hiroaki Ohshima, Yoshiyuki Shoji, Kenro Aihara, Noriko Kando

Proceedings of the 2021 International Conference on Multimedia Retrieval, Aug 24, 2021 Peer-reviewed
MTUNet: Few-Shot Image Classification With Visual Explanations.

Bowen Wang, Liangzhi Li, Manisha Verma, Yuta Nakashima, Ryo Kawasaki, Hajime Nagahara

IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2294-2298, Jun, 2021 Peer-reviewed
SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition.

Liangzhi Li, Bowen Wang, Manisha Verma, Yuta Nakashima, Ryo Kawasaki, Hajime Nagahara

2021 IEEE/CVF International Conference on Computer Vision(ICCV), 1026-1035, 2021
Noisy-LSTM: Improving Temporal Awareness for Video Semantic Segmentation

Bowen Wang, Liangzhi Li, Yuta Nakashima, Ryo Kawasaki, Hajime Nagahara, Yasushi Yagi

IEEE Access, 9 46810-46820, 2021 Peer-reviewed
SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition.

Liangzhi Li, Bowen Wang, Manisha Verma, Yuta Nakashima, Ryo Kawasaki, Hajime Nagahara

CoRR, abs/2009.06138, 2020 Peer-reviewedLead authorCorresponding author
Joint Learning of Vessel Segmentation and Artery/Vein Classification with Post-processing.

Liangzhi Li, Manisha Verma, Yuta Nakashima, Ryo Kawasaki, Hajime Nagahara

Medical Imaging with Deep Learning, abs/2005.13337 440-453, 2020 Peer-reviewedLead authorCorresponding author
IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks.

Liangzhi Li, Manisha Verma, Yuta Nakashima, Hajime Nagahara, Ryo Kawasaki

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 3645-3654, 2020 Peer-reviewedLead authorCorresponding author
Sustainable CNN for Robotic: An Offloading Game in the 3D Vision Computation.

Liangzhi Li, Kaoru Ota, Mianxiong Dong

IEEE Trans. Sustain. Comput., 4(1) 67-76, 2019 Peer-reviewedLead author
Enabling 60 GHz Seamless Coverage for Mobile Devices: A Motion Learning Approach.

Liangzhi Li, Kaoru Ota, Mianxiong Dong, Christos V. Verikoukis

2018 IEEE Global Communications Conference (GLOBECOM), 1-6, 2018 Peer-reviewedLead author
Humanlike Driving: Empirical Decision-Making System for Autonomous Vehicles.

Liangzhi Li, Kaoru Ota, Mianxiong Dong

IEEE Trans. Vehicular Technology, 67(8) 6814-6823, 2018 Peer-reviewedLead author
Deep Learning for Smart Industry: Efficient Manufacture Inspection System With Fog Computing.

Liangzhi Li, Kaoru Ota, Mianxiong Dong

IEEE Trans. Ind. Informatics, 14(10) 4665-4673, 2018 Peer-reviewedLead author
DeepNFV: A Lightweight Framework for Intelligent Edge Network Functions Virtualization.

Liangzhi Li, Kaoru Ota, Mianxiong Dong

IEEE Network, 33(1) 136-141, 2018 Peer-reviewedLead author
Human in the Loop: Distributed Deep Model for Mobile Crowdsensing.

Liangzhi Li, Kaoru Ota, Mianxiong Dong

IEEE Internet Things J., 5(6) 4957-4964, 2018 Peer-reviewedLead author
Everything is Image: CNN-based Short-Term Electrical Load Forecasting for Smart Grid.

Liangzhi Li, Kaoru Ota, Mianxiong Dong

2017 11th International Conference on Frontier of Computer Science and Technology, 344-351, 2017 Peer-reviewedLead author
Eyes in the Dark: Distributed Scene Understanding for Disaster Management.

Liangzhi Li, Kaoru Ota, Mianxiong Dong, Wuyunzhaola Borjigin

IEEE Trans. Parallel Distrib. Syst., 28(12) 3458-3471, 2017 Peer-reviewedLead author
Smooth Sensor Motion Planning for Robotic Cyber Physical Social Sensing (CPSS).

Hong Tang 0003, Liangzhi Li, Nanfeng Xiao

Sensors, 17(2) 393-393, 2017 Peer-reviewedCorresponding author
When Weather Matters: IoT-Based Electrical Load Forecasting for Smart Grid.

Liangzhi Li, Kaoru Ota, Mianxiong Dong

IEEE Communications Magazine, 55(10) 46-51, 2017 Peer-reviewedLead author
Volumetric view planning for 3D reconstruction with multiple manipulators.

Liangzhi Li, Nanfeng Xiao

Ind. Robot, 42(6) 533-543, 2015 Peer-reviewedLead authorCorresponding author

Misc.

Cardiovascular Disease Risk Prediction using Retinal Images via Explainable-AI based models with Traditional CVD risk factor estimation

Ryo Kawasaki, Yiming Qian, Liangzhi Li, Kohji Nishida, Yuta Nakashima, Hajime Nagahara

INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 63(7), Jun, 2022 Peer-reviewed
A fully automated grading system for the retinal arteriovenous crossing signs using deep neural network

Kawasaki, Ryo, Li, Liangzhi, Nakashima, Yuta, Nagahara, Hajime, Ohkubo, Takayoshi, Nishida, Kohji

Investigative Ophthalmology & Visual Science, 61(7) 1930-1930, 2020 Peer-reviewed

Professional Memberships

2017 - Present

Institute of Electrical and Electronics Engineers (IEEE)

Research Projects

Risk profiling for cardiovascular diseases using the retinal images

Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (B), Japan Society for the Promotion of Science, Apr, 2022 - Mar, 2026
Explainable Artificial Intelligence for Medical Applications

科学研究費助成事業若手研究, 日本学術振興会, Apr, 2021 - Mar, 2023

李良知
Removing the Burden of Data Labeling: Automatic Surgical Video Understanding with Unsupervised Learning

科学研究費助成事業研究活動スタート支援, 日本学術振興会, Sep, 2020 - Mar, 2022

李良知

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