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齐强

职称: 特聘副教授
学院: 数据科学学院
电子邮箱: qiangq@qust.edu.cn
  • 基本信息

  • 项目

  • 获奖

  • 论文

  • 专利

  • 课程

  • 教材或专著

  • 基本信息
    姓名:  齐强        最高学位:博士               入职科大时间:2024.03          
    主要研究方向:计算机视觉、人工智能、虚拟现实、目标检测和识别           导师类别:硕士生导师          
    国内外重要学术组织任职: 中国计算机学会会员、IEEE会员;IEEE Transactions on Neural Networks and Learning Systems、IEEE Transactions on Intelligent Transportation System、IEEE Transactions on Circuits and Systems for Video Technology等国际期刊审稿人。
    其他情况简介:

    以第一作者身份在国际权威期刊IEEE Transactions on Image Processing (TIP)、IEEE Transactions on Multimedia(TMM)、IEEE Transactions on Intelligent Transportation Systems (TITS)、IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) 上发表了多篇具有代表性的研究成果。

    目前课题组涉及理论问题研究(纵向项目)和一些实际工程应用(横向项目),十分欢迎学习态度认真、动手能力好、团队意识强的同学加入课题组。我希望我的学生和我一起努力做出一流水平的研究,并写出高质量的学术论文。也特别鼓励我的学生(我也会尽我最大努力帮助我的学生)在毕业后读硕士或博士、到公司从事技术和研发工作。 欢迎对我的研究方向感兴趣的同学与我联系(请直接邮件联系)。

    学习研究经历:
    2019/09-2023/12:厦门大学,计算机科学与技术系,博士
    2015/09-2018/06:中国海洋大学,计算机科学与技术系,硕士
  • 项目
    [1]省部级,福厦泉国家自主创新示范区数据安全与视觉分析核心技术研究协同创新平台项目(3502ZCQXT2022008),2023年1月-2024年12月,200万,在研,技术骨干
    [2]之江实验室,面向复杂异构数据的联邦学习方法研究(2021KB0AB03),2021年1月-2022年12月,50万,结题,技术骨干
    [3]厦门大学校长基金,面向非独立同分布长尾数据的联邦学习方法研究(20720210099),2021年1月-2022年12月,15万,结题,技术骨干
  • 获奖
  • 论文
    [1] Q. Qi, T. Hou, Y. Lu, Y. Yan, and H. Wang. DGRNet: A Dual-Level Graph Relation Network for Video Object Detection. IEEE Transactions on Image Processing (TIP), 2023, 32: 4128-4141. (CCF A 类期刊、SCI/JCR 一区 Top 期刊,Impact Factor: 10.6)
    [2] Q. Qi, Y. Yan, and H. Wang. Class-Aware Dual-Supervised Aggregation Network for Video Object Detection. IEEE Transactions on Multimedia (TMM), 2024, 26: 2109-2123. (SCI/JCR 一区 Top 期刊,Impact Factor: 7.3)
    [3] Q. Qi, X. Wang, T. Hou, Y. Yan, and H. Wang. FastVOD-Net: A Real-Time and High- Accuracy Video Object Detector. IEEE Transactions on Intelligent Transportation Systems (TITS), 2022, 23(11): 20926-20942. (SCI/JCR 一区 Top 期刊,Impact Factor: 8.5)
    [4] Q. Qi, T. Hou, Y. Yan, Y. Lu, and H. Wang. TCNet: A Novel Triple-Cooperative Network for Video Object Detection. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2023, 33(8): 3649-3662. (SCI/JCR 一区 Top 期刊, Impact Factor: 8.4)
    [5] Q. Qi, M. Jian, Y. Yin, J. Dong, W. Zhang, and H. Yu. Saliency Detection Using Texture and Local Cues. CCF Chinese Conference on Computer Vision (CCCV), 2017: 689-699.
    [6] Q. Qi, M. Jian, Y. Yin, J. Dong, W. Zhang, and H. Yu. Saliency Detection via Combining Global Shape and Local Cue Estimation. International Conference on Intelligent Science and Big Data Engineering (IScIDE), 2017: 325-334.
    [7]M. Jian, Q. Qi, H. Yu, J. Dong, C. Cui, X. Nie, H. Zhang, Y. Yin, and K. Lam. The Extended Marine Underwater Environment Database and Baseline Evaluations. Applied Soft Computing (ASOC), 2019, 80: 425-437. (SCI/JCR一区Top期刊,Impact Factor: 8.7)
    [8]T. Hou, Q. Qi, Y. Lu, K. Du, and H. Wang. Dual Selection Network for Video Object Detection. IEEE International Conference on Multimedia and Expo (ICME), 2022, DOI: 10.1109/ICME52920.2022.9859947. (CCF B 类会议,Oral)
    [9] Jian M, Qi Q, Dong J, et al. The OUC-Vision Large-Scale Underwater Image Database. IEEE International Conference on Multimedia and Expo (ICME), 2017: 1297-1302. (CCF B 类会议)
    [10] Z. Qiu, Q. Qi, Y. Lu, Y. Yan, and H. Wang. Proposal Distillation of Multi-Modal Feature Aggregation Network for Video Object Detection. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024. (CCF B类会议)
    [11]Jian M, Qi Q, Dong J, et al. Saliency Detection Using Quaternionic Distance Based Weber Local Descriptor and Level Priors. Multimedia tools and applications, 2018, 77: 14343-14360.
    [12] Jian M, Qi Q, Dong J, et al. Integrating QDWD With Pattern Distinctness and Local Contrast for Underwater Saliency Detection. Journal of Visual Communication and Image Representation, 2018, 53: 31-41.
    [13] Z. Qiu, Q. Qi, Y. Yan, and H. Wang. DF-Net: Diversity-Focused Network for Video Object Detection. International Conference on Image Processing (ICIP), 2023, DOI: 10.1109/ICIP49359.2023.10223065. (CCF C 类会议)
    [14] H. Ye, Q. Qi, Y. Wang, Y. Lu, and H. Wang. Global and Local Feature Alignment for Video Object Detection. ACM International Conference on Multimedia in Asia (MMAsia), 2021, DOI: 10.1145/3444685.3446263. (CCF C 类会议)
    [15] Jian M, Qi Q, Dong J, et al. Saliency Detection Using Quatemionic Distance Based Weber Descriptor and Object Cues. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA). 2016: 1-4.
    [16] X. Wang, F. Gao, J. Dong, and Q. Qi. Change Detection for Synthetic Aperture Radar Images Based on Pattern and Intensity Distinctiveness Analysis. International Conference on Graphic and Image Processing (ICGIP), 2018, 10615: 1209-1215.
  • 专利
  • 课程
  • 教材或专著