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介绍 Introduction

This lab focuses on artificial intelligence and its application to ocean.

本实验室的研究主要关注人工智能以及其在海洋方面的应用。

Zhibin Yu, PhD, Lecturer, Department of Electronic Engineering, College of Information Science and Engineering, Ocean University of China.

俞智斌,博士,讲师,中国海洋大学信息科学与工程学院电子系。

教育背景 Education Background

Apr. 2016 ~ now: Lecturer. in the Department of Electronic and Engineering, College of Information Science and Engineering, Ocean University of China. Research Interests: The aplication of artificial neural network on underwater vision.

Mar. 2011 ~ Feb. 2016: D.E. in the School of Electronic and Engineering, Kyungpook National University. Research Interests: Artificial neural network and its application.

Mar. 2009 ~ Feb. 2011: M.E. in the School of Computer Science and Engineering, Kyungpook National University. Research Interests: Machine learning and its application.

Sep. 2001 ~ Jun. 2005: B.E in the School of Thermal Engineering, Harbin Institute of Technology.

2016年4月 ~ 现在: 中国海洋大学信息科学与工程学院电子系,讲师,研究方向:人工神经网络在水下视觉方面的应用

2011年3月 ~ 2016年2月: 庆北国立大学电子电器计算机学院电子工学部,工学博士,研究方向:人工神经网络及其应用

2009年3月 ~ 2011年2月: 庆北国立大学电子电器计算机学院计算机工学部,工学硕士,研究方向:机器学习及其应用

2001年9月~ 2005年6月:哈尔滨工业大学热能与动力工程|工学学士

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期刊审稿 Journal Reviews

IEEE Trans. On Neural Networks and Learning Systems

Neural Networks

基金资助 Received Funding

基于对抗生成网络的水下图像生成及应用,国家博士后基金项目,负责人,2018.01-2018.06 直接经费 5万元 公示中

基于深度学习和双目视觉的深度图像估计及水下图像复原,国家科学自然基金青年基金项目,负责人,2018.01-2020.12 直接经费 27.5万元 批准号:61701463

基于深度学习和双目水下RGB图像的深度图像估计及图像复原应用,山东省博士后基金,负责人,2017.09-2019.08 总费用 9万元 批准号:ZR201702150029

基于水下多元图像和深度学习的水体光学参数反演及应用,中央高校基本科研业务费,负责人,2016.10-2018.08 直接经费 10万元 批准号:201713019

Underwater Image Generation Based on Adervesarial Neural Networks, National PostDoctor Foundation of China,Main Investigator, Direct Funding:¥50,000. Public notice

Underwater Depth Map Estimation and Image Restoration Based on Deep Learning and stereo vision, National Natural Science Foundation of China,Main Investigator, Direct Funding:¥275,000. Granted Number: 61701463

The Application Underwater Depth Map Estimation and Image Restoration Based on Deep Learning and Binocular Camera, Natural Science Foundation of Shandong Province of China,Main Investigator, Total Funding:¥90, 000. Granted Number: ZR201702150029

Inherent Optical Parameter Estimation and Application Based on Multivariate Underwater Image and Deep Learning, Fundamental Research Funds for the Central Universities,Main Investigator, Direct Funding:¥100, 000. Granted Number: 201713019

论文 Publications

期刊论文 Journal Papers

Zhibin Yu, Yubo Wang, Bing Zheng, Haiyong Zheng(*), Nan Wang, and Zhaorui Gu, Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network, Computational Intelligence and Neuroscience, Volume 2017 (2017), Article ID 8351232, DOI:10.1155/2017/8351232

Zhibin Yu, Dennis S. Moirangthem, Minho Lee(*). Continuous Timescale Long-Short Term Memory Neural Network for Human Intent Understanding. Frontiers in Neurorobotics, 2017.08 DOI: 10.3389/fnbot.2017.00042

Sangwook Kim, Zhibin Yu, Minho Lee(*). Understanding human intention by connecting perception and action learning in artificialagents. Neural Networks, 2017.02 DOI: 10.1016/j.neunet.2017.01.009

Bing Zheng, Nan Wang(*), Haiyong Zheng, Zhibin Yu, and Jinpeng Wang. Object extraction from underwater images through logical stochastic resonance. Optics Letters, 2016.11 DOI: 10.1364/OL.41.004967

Zhibin Yu and Minho Lee(*). Human Motion Based Intent Recognition Using a Deep Dynamic Neural Model. Robotics and Autonomous System, 2015.09 DOI: 10.1016/j.robot.2015.01.001

Zhibin Yu, Minho Lee(*). Real-Time Human Action Classification Using a Supervised Dynamic Neural Model. Neural Networks, 2015.09 DOI:10.1016/j.neunet.2015.04.013

Sangwook Kim, Zhibin Yu, Rhee Man Kil and Minho Lee(*), Deep Learning of Support Vector Machines with Class Probability Output Networks, Neural Networks, 2015.04 DOI:10.1016/j.neunet.2014.09.007

会议论文 Conference Papers

Shanchen Jiang, Fengna Sun, Zhaorui Gu, Haiyong Zheng, Wang Nan, Zhibin Yu(*), Underwater 3D reconstruction based on laser line scanning, OCEANS 2017, Aberdee, United Kingdom, 2017.6, DOI: 10.1109/OCEANSE.2017.8084737

Li Ma, Min Fu, Nan Wang, Haiyong Zheng(*), Zhibin Yu, Zhaorui Gu, Jia Yu; Bing Zheng; Xuefeng Liu,Simulation of stochastic resonance in underwater laser communication, OCEANS 2017, Aberdee, United Kingdom, 2017.6, DOI: 10.1109/OCEANSE.2017.8084737

Zhibin Yu, Sangwook Kim, and Minho Lee(*), Human Intention Understanding Based On Object Affordance and Action Classification. IJCNN 2015 DOI:10.1109/IJCNN.2015.7280587

Zhibin Yu, Rammohan Mallipeddi, Minho Lee(*), A fast training algorithm of multiple-timescale recurrent neural network for agent motion generation, 3rd International Conference on Human-Agent Interaction, HAI 2015, Daegu, Republic of Korea, 2015.10. DOI:10.1145/2814940.2814986

Sangwook Kim, Zhibin Yu, Jonghong Kim, Amitash Ojha, Minho Lee(*), Human-robot interaction using intention recognition, 3rd International Conference on Human-Agent Interaction, HAI 2015, Daegu, Republic of Korea, 2015.10 DOI:10.1145/2814940.2815002

Zhibin Yu, Rammohan Mallipeddi and Minho Lee(*), Supervised Multiple Timescale Recurrent Neuron Network Model for Human Action Classification, 20th International Conference on Neural Information Processing, ICONIP 2013, Republic of Korea, 2013.11:10.1007/978-3-642-42042-9_25

Jihun Kim, Sungmoon Jeong, Zhibin Yu, Minho Lee(*), Multiple timescale recurrent neural network with slow feature analysis for efficient motion recognition, 20th International Conference on Neural Information Processing, ICONIP 2013, Republic of Korea, 2013.11 DOI:10.1007/978-3-642-42042-9_41

Zhibin Yu and Minho Lee(*), Continuous Motion Recognition Using Multiple Time Constant Recurrent Neural Network With a Deep Network Model,Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013, Hefei, China, 2013.10.22 DOI:10.1007/978-3-642-41278-3_15