Quan Zhou (周全)

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Awards

  • Most Influential Paper Award for IEEE International Conference Image Processing , IEEE Signal Processing Soceity, 2024. (IEEE ICIP最具影响力论文奖)

  • Vice President of Science and Technology, Department of Science and Technology of Jiangsu Province, 2023.(江苏省“科技副总”)

  • Outstanding Contribution Award, IEEE/SPIE International Symposium on Artificial Intelligence and Robotics, 2022.

  • Excellent Yong Backbone Teachers——"Qinglan Project" of Jiangsu Province, Department of Education of Jiangsu Province，2020.(江苏省“青蓝工程”优秀青年骨干教师)

  • Nomination Award for Excellent Master's Thesis (Supervisor), Artificial Intelligence Society of Jiangsu Province，2019.(江苏省人工智能学会优秀硕士论文提名奖)

  • Best paper award, Weighted linear multiple kernel learning for saliency detection. EAI International Conference on Robotic Sensor Networks，2018.

  • Best student paper award, Scene relighting using a single reference image through material constrained layer decomposition. IEEE/SPIE International Symposium on Artificial Intelligence and Robotics，2017.


Invited Talks

  • Dual-path Network: New Paradigm for Real-time Object Detection via High Efficient Attention Computation, Online Famous Master Lecture Hall of CSIG, June, 2024.

  • High speed vs. High accuracy: Real-time Image Semantic understanding, Online Famous Master Lecture Hall of CSIG, April, 2024.

  • High speed vs. High accuracy: Real-time Image Semantic understanding, Intelligent Robotics Forum of IEEE/SPIE International Society on Artificial Intelligence and Robotics, Sanya, November, 2023.

  • Lightweight Neural Network for Real-time Semantic Segmentation, Hubei Key Laboratory of Advanced Control Intelligence Automation for Complex Systems, China University of Geosciences(Wuhan), July, 2019.

  • Contextual based Image Understanding, EAI International Conference on Robotic Sensor Networks, Kitakyushu, Japan, August, 2017.

  • Multi-sacle Context for Image Labeling, Department of Computer Science and Big Data, Guizhou Normal Univeristy, 2016.

  • Multi-sacle Context for Image Labeling via Flexiable Segmentation Graph, Department of Electronics and Information, Wuhan Univeristy, June, 2016.

  • Multi-sacle Context for Image Labeling via Flexiable Segmentation Graph, School of Mathmatics and Statistics, Jiangsu Normal Univeristy, May, 2016.