罗烨

博士、助理教授

办公室:  济事楼314

电邮:      yeluo@tongji.edu.cn

 

主讲课程:                             研究方向: 

 数字图像处理                         视觉显著性检测及分析

 高级数字图像处理                  行为识别、视频中的异常行为检测等 

                             

 

部分科研项目

   

  1. 同济大学青年优秀人才培养计划:  基于深度学习的视觉注视点转移预测模型研究  2018/01-2019/12 主持
  1. 国家自然科学基金面上项目 5177843     城市防灾设施系统失效级联机理与规划优化方法研究  2018/01-2021/12 参与
  2. 国家自然科学基金面上项目 61672380    基于深度神经网络的图像中雾霾的度量与去除 2017/01-2020/12  参与
  3. 国家自然科学基金面上项目 61572362    大数据流中低层与高层惊奇事件检测的研究 2016/01-2019/12   排名第二
  4. 国家自然科学基金 面上项目 81571347   眼动追踪测量在神经行为障碍与退行性疾病早期诊断中的作用研究  2016/01-2019/12     排名第二

 

部分论文 (* indicates corresponding author)

Journals

  1. Dandan Zhu, Lei Dai, Ye Luo*, Xuan Shao, Qiangqiang Zhou, Laurent Itti, Jianwei Lu*, "Salient Object Detection via a Local and Global Method based on Deep Residual Network," in Journal of Visual Communication and Image Representation (JVCI), 2018, in press. (SCI)
  2. Dandan Zhu, Lei Dai, Xuan Shao, Qiangqiang Zhou, Laurent Itti, Ye Luo*, Jianwei Lu, "Image salient object detection with refined deep features via convolution neural network," J. Electron. Imaging 26(6), 063018 (2017), doi: 10.1117/1.JEI.26.6.063018. (SCI)
  3.  Ye Luo, Junsong Yuan, Jianwei Lu. “Finding Spatio-temporal Salient Paths for Video Objects Discovery”. in Journal of Visual Communication and Image Representation (JVCI) Vol. 38, pp. 45-54, 2016. ( SCI, IF: 1.53
  4.  Ye Luo, Junsong Yuan, Ping Xue and Qi Tian, “Saliency Density Maximization for Efficient Visual Objects Discovery”, in IEEE Trans. on Circuits and System for Video Technology (TCSVT), Vol. 21, pp. 1822-1834, 2011. (SCI, IF: 2.259)

International Conferences

  1. Dandan Zhu, Ye Luo*, Lei Dai, Xuan Shao, Laurent Itti, Jianwei Lu. Deep Salient Object Detection via Hierarchical Network Learning. In:  International Conference on Neural Information Processing (ICONIP), 2017. (EI, CCF-C)
  2. Liechuan, Ou, Zheng Chen, Jianwei Lu, Ye Luo*. Regularizing CNN via Feature Augmentation. In: International Conference on Neural Information Processing (ICONIP), 2017. (EI, CCF-C)
  3. Xuan Shao, Ye Luo*, Dandan Zhu, Shuqin Li, Laurent Itti, Jianwei Lu. Scanpath Prediction Based on High-level Features and Memory Bias. In: International Conference on Neural Information Processing (ICONIP), 2017. (EI, CCF-C)
  4. Xiao Liu, Ye Luo, Yu Ye, and Jianwei Lu. MC-DCNN: Dilated Convolutional Neural Network for Computing Stereo Matching Cost. In: International Conference on Neural Information Processing (ICONIP), 2017. (EI, CCF-C)
  5. Yixuan Xu, Ye Luo, Yuan Li, Guokai Zhang, Jianwei Lu. A Hybrid Model: DGnet-SVM for the Classification of Pulmonary Nodules. In: International Conference on Neural Information Processing (ICONIP), 2017. (EI, CCF-C)
  6. Dandan Zhu, Ye Luo*, Xuan Shao, Laurent Itti, Jianwei Lu, “SALIENCY PREDICTION BASED ON NEW DEEP MULTI-LAYER CONVOLUTION NEURAL NETWOR”, in ICIP, 2017. (EI, CCF-C)
  7.  Ye Luo, Loong-Fah Cheong and Tran Lam An, “Actionness-assisted Recognition of Actions”, in International Conference on Computer Vision (ICCV) 2015, pp. 3244-3252. (EI, CCF-A)
  8.  Ye Luo, Loong-Fah Cheong and John-John Cabibihan, “Model the Temporality of Saliency”, Asian Conference on Computer Vision (ACCV) 2014, Vol. 9005, pp. 205-220. (EI, CCF-C)
  9.  Ye Luo, Junsong Yuan and Qi Tian, “Salient Object Detection in Videos by Optimal Spatial-temporal Path Discovery”, ACM multimedia 2013, pp. 509-512. (EI, CCF-A)
  10.  Ye Luo, Junsong Yuan, Ping Xue and Qi Tian, “Salient Region Detection and Its Application to Video Retargeting”, in IEEE Conference on Multimedia Expo (ICME’11), pp. 1-6, 2011. (EI, CCF-B)

 

学术活动

  • IEEE Member, CCF Member
  • 学术期刊会议审稿人
    • IEEE Transaction on Circuits and Systems for Video Technology
    • Signal Processing: Image Communication
    • the Visual Computer
    • IEEE Signal Processing Letter
    • Neurocomputing
    • Computer Vision and Image Understanding
    • IEEE Access
    • ICPR2018, ICIP2018, ICIP2017, ICME 2015, ICME 2014, ACCV 2010

 

获奖经历

  1. 2015.11 获得国际计算机视觉顶级会议ICCV的优秀青年研究者奖
  2.  新加坡南洋理工大学博士研究生全额奖学金
  3. 安徽大学优秀毕业生

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