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34th MHS 2023: Nagoya, Japan
- International Symposium on Micro-NanoMehatronics and Human Science, MHS 2023, Nagoya, Japan, November 20-22, 2023. IEEE 2023, ISBN 979-8-3503-1507-3
- Jacinto Colan, Ana Davila, Yasuhisa Hasegawa:
Enhancing Gradient-Based Inverse Kinematics with Dynamic Step Sizes. 1-6 - Dezhi Song, Yongxiang Song, Di Wu, Xiangyu Luo, Chaoyang Shi:
Development of a Liquid-Metal-Enhanced Continuum Joint with Variable Stiffness Capability for Flexible Endoscopy. 1-6 - Pengfei Zhang, Xiong Cheng, Yao Ma, Jun Liu, Liyan Zhu, Daying Sun, Xiaodong Huang:
Efficient and Accurate Design of Infrared and Laser-Compatible Stealth Metasurface Using Bidirectional Artificial Neural Network. 1-5 - Jian Wang, Yao Ma, Liyan Zhu, Xiaodong Huang:
High-Performance All-Solid-State Micro-Supercapacitor by Using Oxygen Plasma Treatement on LiPON Electrolyte. 1-4 - Zihao Dong, Jian Huang, Haoyuan Wang, Bo Yang, Dongrui Wu, Yaonan Zhu, Yasuhisa Hasegawa:
Deformable Object Manipulation Using Human Demonstration Enhanced Deep Deterministic Policy Gradient. 1-6 - Takahiro Ikeda, Satoshi Ueki, Hironao Yamada:
Comparison of User Interfaces for Semi-Automatic Visual Support System Using Drone for Teleoperated Construction Robot. 1-6 - Haruki Nakano, Yuiki Yamasaki, Shuichi Wakimoto, Takefumi Kanda, Daisuke Yamaguchi:
Development of Robotic Hand Using Dual-Directional Bending Soft Fingers and Bellows Suction Mechanism. 1-5 - Guangyi Zhang, Sheng Zeng, Liang Fang, Zhan Yang:
A Light-Weight Convolutional Neural Network for Super-Resolving SEM Images to Enhance Real-Time Micro-Nano Manipulation. 1-6 - Kanji Kaneko, Mamiko Tsugane, Yosuke Hasegawa, Takeshi Hayakawa, Hiroaki Suzuki:
Experimental and Numerical Investigation of Particle Capture for Agglutination-Based NP detection Using the Vibration-Induced Flow. 1-4 - Ana Davila, Jacinto Colan, Yasuhisa Hasegawa:
Gradient-Based Fine-Tuning Strategy for Improved Transfer Learning on Surgical Images. 1-5 - Jiaxing Tian, Jun Izawa:
Study on High-Level Structure of cognition control construction in Exploration and Exploitation within Multi-Armed Bandit Model of Reinforcement Learning. 1-6 - Tomu Makino, Tetsuya Hasegawa, Shouhei Shirafuji, Jun Ota, Arito Yozu:
Evaluation of the Giving-Way-Prevention Function of a Soft Exosuit Incorporating the Multi-articular Muscle Mechanism. 1-5
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