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Hyunseok Yang

Researcher at Yonsei University

Publications -  181
Citations -  1285

Hyunseok Yang is an academic researcher from Yonsei University. The author has contributed to research in topics: Holographic Data Storage System & Actuator. The author has an hindex of 18, co-authored 177 publications receiving 1157 citations.

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Improving the vehicle performance with active suspension using road-sensing algorithm

TL;DR: The road-sensing system which can robustly reconstruct the road input profiles from the intermixed data with the vehicle's dynamic motion, is implemented using the composite-sensor system with the optimally shaped transfer function.
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Normal-Force Control for an In-Pipe Robot According to the Inclination of Pipelines

TL;DR: A method is proposed to estimate the relative attitude between the robot's main body and the pipe using the angular sensors attached to a pantograph mechanism so that the robot can control its normal force according to the variation in pipe inclination.
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Variable stiffness mechanism for human-friendly robots

TL;DR: In this article, a variable stiffness mechanism (VSM) for human-friendly robots was developed to simultaneously meet safety and performance needs, which has high stiffness in normal operation mode and low stiffness in collision mode when the load applied to the joint exceeds a critical load.
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Novel mechanisms and simple locomotion strategies for an in-pipe robot that can inspect various pipe types

TL;DR: In this paper, a pipe inspection robot that can travel through various pipe configurations including vertical, elbow, and branch pipes is presented, where two specific mechanisms in the robot are important for successful locomotion: the Adaptable Quad Arm Mechanism (AQAM) and the Swivel Hand Mechanism(SHM).
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Speckle noise reduction for digital holographic images using multi-scale convolutional neural networks.

TL;DR: A fast speckle noise reduction method with only a single reconstructed image based on convolutional neural networks that has multi-sized kernels that can capture the speckled noise component effectively from digital holographic images is proposed.