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Yixin Zhu

Publications

Citations

1,021

Publications by Year

20152025

Co-Authors:

Kaspar AlthoeferZhexuan CaoYixin ChenBoyuan ChenChi Chu

Show All Co-Authors (103)

Yixin Zhu

Affiliation

Institute for Artificial Intelligence

Peking University

Beijing, China

Publication Topics

Point Cloud,
3D Scene,
Contact Point,
Human Motion,
Latent Space,
Motion Generation,
Robot Manipulator,
Diffusion Model,
Human Pose,
Imitation Learning,
Manipulation Tasks,
Motion Sequences

Biography

Yixin Zhu received the Ph.D. degree (advised by Prof. Song-Chun Zhu) from University of California, Los Angeles (UCLA), Los Angeles, CA, USA, in 2018.,He is an Assistant Professor and the Assistant Dean with the Institute for Artificial Intelligence, Peking University, Beijing, China. His research interest focuses on building interactive AI by integrating high-level common sense (functionality, affordance, physics, causality, and intent) with raw sensory inputs (pixels and haptic signals) to enable richer representation and cognitive reasoning on objects, scenes, shapes, numbers, and agents.(Based on document published on 28 November 2024).

Publications

Citations

1,021

Publications by Year

20152025

Co-Authors:

Kaspar Althoefer
Zhexuan Cao
Yixin Chen
Boyuan Chen
Chi Chu

Show All Co-Authors (103)

Author's Published Works

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Showing 1-3 of 3 results

Conferences (3)

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Seung-Soo Han(3)
Hee-Seung Yoon(3)
Hyeong-Gyun Kim(2)
Ji-Hyun Yoo(2)
Hyun-Il Yoon(1)
Dept. of Information and Communication Engineering, Myongji University, Yongin, Gyeonggi-do, Republic of Korea(1)
Dept. of Information and Communication Engineering, Myongji University, Yongin, Republic of Korea(1)
Department of Information and Communications Engineering, Myongji University, Yongin, Kyunggi-Do, Korea(1)
2019 19th International Conference on Control, Automation and Systems (ICCAS)(1)
2019 1st International Conference on Electrical, Control and Instrumentation Engineering (ICECIE)(1)
2019 International Conference on Electronics, Information, and Communication (ICEIC)(1)
IEEE(3)
Auckland, New Zealand(1)
Jeju, Korea (South)(1)
Kuala Lumpur, Malaysia(1)
Accelerometer(2)
Central Point(2)
Clustering Algorithm(2)
Predictive Maintenance(2)
Semiconductor Industry(2)

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Results

Optimization of Hyper-parameter for CNN Model using Genetic Algorithm

Ji-Hyun Yoo;Hyun-il Yoon;Hyeong-Gyun Kim;Hee-Seung Yoon;Seung-Soo Han

2019 1st International Conference on Electrical, Control and Instrumentation Engineering (ICECIE)

Year: 2019 | Conference Paper |

Cited by: Papers (12)

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Recently CNN is not only widely used in the field of image recognition but also used in various fields such as classifying vibration data. Therefore, increasing the performance of CNN models is becoming more important. One of the various methods to improve the performance of CNN models is to optimize hyper-parameters. This paper presents a method for optimizing the hyper-parameters of CNN models t...Show More

Optimization of Hyper-parameter for CNN Model using Genetic Algorithm

Ji-Hyun Yoo;Hyun-il Yoon;Hyeong-Gyun Kim;Hee-Seung Yoon;Seung-Soo Han

2019 1st International Conference on Electrical, Control and Instrumentation Engineering (ICECIE)

Year: 2019 | Conference Paper |

Clustering Parameter Optimization of Predictive Maintenance Algorithm for Semiconductor Equipment Using One-way Factorial Design

Hee-Seung Yoon;Seung-Soo Han

2019 19th International Conference on Control, Automation and Systems (ICCAS)

Year: 2019 | Conference Paper |

Cited by: Papers (2)

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In this paper, the predictive maintenance(PdM) technology was applied to the semiconductor manufacturing equipment and the DBSCAN algorithm parameters were optimized. The data obtained from the semiconductor equipment was obtained using acceleration sensors and was used to determine the conditions of the equipment. To simulate the malfunction condition of the equipment, the virtual error data was ...Show More

Clustering Parameter Optimization of Predictive Maintenance Algorithm for Semiconductor Equipment Using One-way Factorial Design

Hee-Seung Yoon;Seung-Soo Han

2019 19th International Conference on Control, Automation and Systems (ICCAS)

Year: 2019 | Conference Paper |

Development of Predictive Maintenance Technology for Wafer Transfer Robot using Clustering Algorithm

Hyeong-Gyun Kim;Hee-Seung Yoon;Ji-Hyun Yoo;Hyun-Il Yoon;Seung-Soo Han

2019 International Conference on Electronics, Information, and Communication (ICEIC)

Year: 2019 | Conference Paper |

Cited by: Papers (9)

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Semiconductor equipment is closely related to production yield and should be periodically inspected to maintain the performance. However, traditional equipment maintenance methods have difficulty responding to sudden failures and economic losses due to unpredicted situation. Recently, predictive maintenance technologies have been actively studied, with many advantages, such as the ability to predi...Show More

Development of Predictive Maintenance Technology for Wafer Transfer Robot using Clustering Algorithm

Hyeong-Gyun Kim;Hee-Seung Yoon;Ji-Hyun Yoo;Hyun-Il Yoon;Seung-Soo Han

2019 International Conference on Electronics, Information, and Communication (ICEIC)

Year: 2019 | Conference Paper |

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