• Qiang Fang(方强)

    Associate Professor at NUDT
    Home
    Publications
    Group Members
    Github
    ORCID
    ResearchGate
    • Homepage
    •           
    •           
    •           
    •           
    •           
    •           

    About Me

    •      Now, I am an associate professor at the College of Intelligence Science and Technology, National University of Defense Technology. My research interests include robotics and unmanned aerial vehicles, with a focus on object detection, navigation and reinforcement learning.
    • Email: qiangfang@nudt.edu.cn
    • 还有少量25级硕士招生名额（有科研经历或发表论文者优先），欢迎对科研和学术有强烈兴趣的同学咨询，也欢迎大家推荐！

    Educations

    • Ph.D., Control Science and Engineering, National University of Defense Technology, 2013
    • M.S., Control Science and Engineering, National University of Defense Technology, 2009
    • B.S., Automation, Xidian University, 2007

    News

    • [April 19, 2025] One paper on "Tiny Object Detection" has been accepted by Remote Sensing. Congratulations to Shuohao Shi!
    • [April 12, 2025] "Semi-supervised Object Detection for Remote Sensing Images Using Consistent Dense Pseudo Labels" has been accepted by Remote Sensing. Congratulations to Tong Zhao and Yujun Zeng!
    • [December 9, 2024] "Denser Teacher: Rethinking Dense Pseudo-Label for Semi-supervised Oriented Object Detection" has been accepted by IEEE Transactions on Circuits and Systems for Video Technology(IEEE TCSVT). Congratulations to Tong Zhao!
    • [November 29, 2024] One paper has been accepted by IEEE Transactions on Cognitive and Developmental Systems(IEEE TCDS). Congratulations to Yixing Lan!
    • [June 30, 2024] "Similarity_Distance_Based_Label_Assignment_for_Tiny_Object_Detection" has been accepted by IROS 2024(oral presentation!). Congratulations to Shuohao Shi!.
    • [June 7, 2024] “Density-Guided Dense Pseudo Label Selection For Semi-supervised Oriented Object Detection” has been accepted by IEEE International Conference on Image Processing (ICIP 2024). Congratulations to Tong Zhao!.
    • [August 15, 2023] “Sample Efficient Deep Reinforcement Learning With Online State Abstraction and Causal Transformer Model Prediction” has been accepted by IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS). Congratulations to Yixing Lan!