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, Associate Professor, College of Electronic Engineering, Division of Information Science and Engineering, Ocean University of China.
俞智斌，博士，副教授，中国海洋大学信息科学与工程学部电子工程学院。
Jan. 2020 ~ now: Associate Professor. 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.
Apr. 2016 ~ Dec. 2019: 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.
2020年1月 ~ 现在: 中国海洋大学信息科学与工程学部电子工程学院，副教授，研究方向：人工神经网络在在低质图像处理方面的应用
2016年4月 ~ 2019年12月: 中国海洋大学信息科学与工程学院电子系，讲师，研究方向：人工神经网络在低质图像处理方面的应用
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.
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
Applied Softcomputing, Computers & Electrical Engineering, Computer Vision and Image Understanding, Concurrency and Computation: Practice and Experience, IEEE Access, IEEE Trans. on Neural Networks and Learning Systems , IEEE Trans. on Intelligent Transportation Systems, Journal of Electronic Imaging, Mobile Networks and Applications, Neural Networks, Neurocomputing, Neural Processing Letters, Optics and Laser Technology, Pattern Recognition
水下威胁物种智能监测与预警关键技术研究，海南省重点研发计划，负责人，2022.07-2024.06 总费用 238万元 批准号：ZDYF2022SHFZ318
水下语义同步定位与建图系统研发，崖州湾菁英人才项目，负责人，2022.07-2024.06 总费用 30万元 批准号：SCKJ-JYRC-2022-102
基于深度度量学习的高光谱智能目标识别，山东省自然科学基金联合基金，负责人，2022.01-2024.12 总费用 200万元 批准号：ZR2021LZH005
基于元学习的浑浊水体少样本跨域目标检测应用研究，国家科学自然基金面上项目，负责人，2022.01-2025.12 直接经费 56万元 批准号：62171419
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，山东省自然科学基金博士基金，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
Research on key technologies of intelligent monitoring, detection and warning of underwater threat species, Hainan Province Science and Technology Speical Fund, China, Total Funding: ￥2,380,000.00 Granted Number:ZDYF2022SHFZ318
Underwater semantic synchronous positioning and mapping system research and development, Yazhou Bay elite talent project of Sanya, China, Total Funding: ￥300,000.00 Granted Number:SCKJ-JYRC-2022-102
Metric-learning based hyperspectral object detection, Natural Science Foundation of Shandong Province of China, Principal investigator, Total Funding: ￥2,000,000.00 Granted Number: ZR2021LZH005
Meta-learning based underwater cross-domain object detection in a turbid enviroment with few samples, National Natural Science Foundation of China, Principal investigator, Direct Funding: ￥560,000. Granted Number: 62171419
Generative adversarial learning based aquatic creature in-situ detection system research and development, Primary R&D Program of Shandong Province (Public welfare), China, Principal 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, Principal 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,Principal 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, China, Principal 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, China, Principal investigator, Direct Funding: ￥100, 000. Granted Number: 201713019
Hanshu Zhang, Suzhen Fan, Shuo Zou, Zhibin Yu*, Bing Zheng*, Deep underwater image compression for enhanced machine vision applications, Frontiers in Marine Science, Volume 11, 2024, | DOI:10.3389/fmars.2024.1411527
Zhenyu Yang, Yongxin Zhang, Jv Zheng, Zhibin Yu(*) and Bing Zheng, Scale Information Enhancement for Few-Shot Object Detection on Remote Sensing Images, Remote Sensing, 15(22), 2023 | DOI:10.3390/rs15225372
Ziqiang Zheng, Yujie Cheng, Zhichao Xin, Zhibin Yu(*) and Bing Zheng, Robust Perception Under Adverse Conditions for Autonomous Driving Based on Data Augmentation, IEEE Transactions on Intelligent Transportation Systems, Volume 24, Issue 12, 2023 | DOI:10.1109/TITS.2023.3297318
Ziqiang Zheng, Zhichao Xin, Zhibin Yu(*) and Sai-Kit Yeung, Real-time GAN-based Image Enhancement for Robust Underwater Monocular SLAM, Frontiers in Marine Science, Volume 10, 2023 | DOI:10.3389/fmars.2023.1161399
Lu Han, Jiping Zhai, Zhibin Yu(*) and Bing Zheng, See you somewhere in the ocean: Few-shot domain adaptive underwater object detection, Frontiers in Marine Science, Volume 10, 2023 | DOI:10.3389/fmars.2023.1151112
Zhichao Xin, Zhe Wang, Zhibin Yu(*) and Bing Zheng, Shaoda Zhang and Bing Zheng, ULL-SLAM:Underwater low-light enhancement for the front-end of visual SLAM, Frontiers in Marine Science, Volume 10, 2023 | DOI:10.3389/fmars.2023.1133881
Yang Guan, Xiaoyan Liu, Zhibin Yu(*), Yubo Wang, Xingyu Zheng, Shaoda Zhang(*) and Bing Zheng, Fast Underwater Image Enhancement Based on a Generative Adversarial Framework, Frontiers in Marine Science, Volume 9, 2022 | DOI:10.3389/fmars.2022.964600
Yaofeng Xie, Zhibin Yu(*), Xiao Yu and Bing Zheng(*), Lighting the darkness in the sea: A deep learning model for underwater image enhancement, Frontiers in Marine Science, 1470, | DOI:10.3389/fmars.2022.921492
Ziqiang Zheng; Jie Yang; Zhibin Yu(*); Yubo Wang(*); Zhijian Sun; Bing Zheng ; Not every sample is efficient: Analogical generative adversarial network for unpaired image-to-image translation, Neural Networks, 2022, 148: 166-1751 | DOI:10.1016/j.neunet.2022.01.013
Qi Zhao(#), Ziqiang Zheng(#), Huimin Zeng, Zhibin Yu(*), Haiyong Zheng and Bing Zheng, The Synthesis of Unpaired Underwater Images for Monocular Underwater Depth Prediction, Frontiers in Marine Science, 8:690962, | DOI:10.3389/fmars.2021.690962
Qi Zhao, Zhichao Xin, Zhibin Yu(*), Bing Zheng, Unpaired Underwater Image Synthesis with a Disentangled Representation for Underwater Depth Map Prediction, Sensors, 21,9, 3268, | DOI:10.3390/s21093268
Ziqiang Zheng(#), Zhibin Yu(#), Yang Wu, Haiyong Zheng(*), Bing Zheng, Minho Lee(*), Generative Adversarial Network with Multi-branch Discriminator for imbalanced cross-species image-to-image translation, Neural Networks,141, 2021, | DOI: 10.1016/j.neunet.2021.04.013
Ziqiang Zheng, Hongzhi Liu, Fan Yang, Xingyu Zheng, Zhibin Yu(*) and Shaoda Zhang(*),Representation-guided generative adversarial network for unpaired photo-to-caricature translation, Computers & Electrical Engineering, 90, 106999, | DOI: 10.1016/j.compeleceng.2021.106999
Ziqiang Zheng, Zhibin Yu, Haiyong Zheng, Yang Yang(*) and Heng Tao Shen. One-Shot Image-to-Image Translation via Part-Global Learning with a Multi-adversarial Framework. IEEE Transactions on Multimedia, 2021, | DOI: 10.1109/TMM.2021.3053775
Ruyue Han, Yang Guan, Zhibin Yu(*), Peng Liu(*), Haiyong Zheng， Underwater Image Enhancement Based on a Spiral Generative Adversarial Framework, IEEE Access， DOI:10.1109/ACCESS.2020.3041280
Xinliang Zhang(#), Huimin Zeng(#), Xiang Liu, Zhibin Yu(*), Haiyong Zheng, Bing Zheng,In Situ Holothurian Noncontact Counting System: A General Framework for Holothurian Counting, IEEE Access 8, DOI: 10.1109/ACCESS.2020.3038643
Huimin Zeng(#), Xinliang Zhang(#), Zhibin Yu(*), Yubo Wang(*),SR-ITM-GAN: Learning 4K UHD HDR With a Generative Adversarial Network, IEEE Access 8, DOI: 10.1109/ACCESS.2020.3028584
Yubo Wang(#), Zhibin Yu(#), Tatinati Sivanagarajac, Kalyana C.Veluvolud, Fast and accurate online sequential learning of respiratory motion with random convolution nodes for radiotherapy applications. Applied Soft Computing, 95, 106528, DOI: 10.1016/j.asoc.2020.106528
Qingyun Li(#), Zhibin Yu(#), Yubo Wang* and Haiyong Zheng. TumorGAN: A Multi-Modal Data Augmentation Framework for Brain Tumor Segmentation. Sensors, 20(15), 4203., DOI: 10.3390/s20154203
Yan Zhao,Ziqiang Zheng,Chao Wang,Zhaorui Gu,Min Fu,Zhibin Yu(*),Haiyong Zheng,Nan Wang,Bing Zheng, Fine-grained facial image-to-image translation with an attention based pipeline generative adversarial framework,Multimedia Tools and Applications, DOI: 10.1007/s11042-019-08346-x
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
Chao Wang, Wenjie Niu, Yufeng Jiang, Haiyong Zheng(*), Zhibin Yu(*), Zhaorui Gu, Bing Zheng, Discriminative Region Proposal Adversarial Network for High-Quality Image-to-Image Translation, International Journal of Computer Vision (2019), DOI:10.1007/s11263-019-01273-2
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:10.3390/s20154203
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
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
Yaofeng Xie, Lingwei Kong, Kai Chen, Xiao Yu, Zhibin Yu(*), Bing Zheng, UVEB: A Large-scale Benchmark and Baseline Towards Real-World Underwater Video Enhancement. In the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024(CVPR). DOI:10.48550/arXiv.2404.14542
Sainan Zhang, Zhibin Yu(*),An Underwater Features Matching System Integrated with Image Enhancement. In 2023 IEEE 6th International Conference on Electronic Information and Communication Technology (ICEICT). DOI:10.1109/ICEICT57916.2023.10245163
Xin Xu, Zhibin Yu(*),Low-Light Image Enhancement Based on Retinex Theory. In 2023 IEEE 6th International Conference on Electronic Information and Communication Technology (ICEICT). DOI:10.1109/ICEICT57916.2023.10246000
Xinliang Zhang, Shu Yang, Huimin Zeng, Zhibin Yu(*), Haiyong Zheng, Bing Zheng, In-situ holothurian non-contact measurement based on parallel laser beams and semantic segmentation. In Global oceans 2020:Singapore–us gulf coast. DOI:10.1109/IEEECONF38699.2020.9389008
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