信 息 科 学 与 工 程 学 院

College of Information Science and Engineering

厚德笃志,勤思敏行

基本信息

basic information

  • 所在院系(中心): 电子工程系
  • 学历: 博士
  • 政治面貌: 群众
  • 邮件地址: yuzhibin@ouc.edu.cn
  • 办公电话: 15650177229
  • 办公室: 山东省青岛市崂山区松岭路238号信息科学与工程学院南楼A212

俞智斌

Yu ZhiBin

课程介绍

course introduction

高级语言程序设计、面向对象程序设计、程序设计实践、人工智能导论

教育及工作经历

education and work experience

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

研究方向

research direction

深度神经网络、图像转译、类脑计算

研究项目

research project

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 批准号:2017M622277 (主持)

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 (主持)

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 (主持)

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 (主持)

学术成果

academic achievements

期刊论文 Journal Papers

Shaoyong Zhang, Na Li, Chenchen Qiu, Zhibin Yu*, Haiyong Zheng, Bing Zheng, Depth map prediction from a single image with generative adversarial nets, Multimedia Tools and Applications, Accepted, DOI: 10.1007/s11042-018-6694-x

Na Li, Ziqiang Zheng, Shaoyong Zhang, Zhibin Yu, Haiyong Zheng, Bing Zheng, The Synthesis of Unpaired Underwater Images Using a Multistyle Generative Adversarial Network, IEEE Access, In Press, DOI:10.1109/ACCESS.2018.2870854

Ziqiang Zheng , Chao Wang , Zhibin Yu*, Haiyong Zheng*, Bing Zheng, Instance Map Based Image Synthesis With a Denoising Generative Adversarial Network, IEEE Access, 2018 , 6 :33654-33665, DOI:10.1109/ACCESS.2018.2849108

Jingyu Lu, Na Li, Shaoyong Zhang, Zhibin Yu, Haiyong Zheng, Bing Zheng, Multi-scale adversarial network for underwater image restoration, Optics & Laser Technology, In Press, DOI:10.1016/j.optlastec.2018.05.048

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

研究生招生条件

postgraduate admissions conditions

欢迎有科研经历或有python、C++编程基础的同学加入!