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。
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
IEEE Trans. On Neural Networks and Learning Systems
Neural Networks
Neurocomputing
Neural Processing Letters
Computer Vision and Image Understanding
基于对抗生成技术的水产原位检测系统研发，山东省重点研发计划（公益类，负责人，2019.01-2020.12 总费用 15万元 批准号：2019GHY112041
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
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
Generative adversarial learning based aquatic creature in-situ detection system research and development ，Primary R&D Program of Shandong Province (Public welfare)，Main Investigator，2019.01-2020.12 Total Funding: ￥150, 000 Granted Number: 2019GHY112041
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
Peng Liu, Guoyu Wang, Hao Qi, Chufeng Zhang, Haiyong Zheng, Zhibin Yu (*), Underwater Image Enhancement With a Deep Residual Framework,IEEE Access, DOI: 10.1109/ACCESS.2019.2928976
Jingyu Lu, Na Li, Shaoyong Zhang, Zhibin Yu(*), Haiyong Zheng, Bing Zheng, Multi-scale adversarial network for underwater image restoration, Optics & Laser Technology, Volume 110, 2019.02, Pages 105-113, DOI:10.1016/j.optlastec.2018.05.048
Chenchen Qiu, Shaoyong Zhang, Chao Wang, Zhibin Yu, Haiyong Zheng(*), Bing Zhenga. Improving Transfer Learning and Squeeze-and-Excitation Networks for Small-scale Fine-grained Fish Image Classification, IEEE Access, DOI: 10.1109/ACCESS.2018.2885055
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, 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, 2018, 11:54241-54257, 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
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
Hao Ding, Bin Wei, Ning Tang, Zhibin Yu, Nan Wang, Haiyong Zheng(*), Bing Zheng, Plankton Image Classification via Multi-Class Imbalanced Learning, 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO), DOI: 10.1109/OCEANSKOBE.2018.8559238
Chao Wang, Xueer Zheng, Chunfeng Guo, Zhibin Yu, Jia Yu, Haiyong Zheng(*), Bing Zheng, Transferred Parallel Convolutional Neural Network for Large Imbalanced Plankton Database Classification, 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO), DOI: 10.1109/OCEANSKOBE.2018.8558836
Jinna Cui, Bin Wei, Chao Wang, Zhibin Yu, Haiyong Zheng(*), Bing Zheng, Hua Yang, Texture and Shape Information Fusion of Convolutional Neural Network for Plankton Image Classification, 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO), DOI: 10.1109/OCEANSKOBE.2018.8559156
Jing Liu, Angang Du, Chao Wang, Zhibin Yu, Haiyong Zheng(*), Bing Zheng, Hao Zhang, Deep Pyramidal Residual Networks for Plankton Image Classification, 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO),DOI: 10.1109/OCEANSKOBE.2018.8559106
Ziqiang Zheng, Chunfeng Guo, Xueer Zheng, Zhibin Yu(*), Weiwei Wang, Haiyong Zheng, Min Fu,Bing Zheng, Fish Recognition from a Vessel Camera Using Deep Convolutional Neural Network and Data Augmentation, 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO). DOI: 10.1109/OCEANSKOBE.2018.8559314
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