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陈龙彪
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副教授
- 出生日期：1987-03-11
- 电子邮箱：9fe015510af205fc2f994e5651e3480dd89a0550220c9989210e50ca90995765143cf622a427d796da9b2976557a6e5a549ef10c54bd684d16bfe68971dcc4bf088d4d071d8167e14cbd362dea02195c6c6304a7ca4268a0546b326d6b9cd913f0b58b3c1dd1bb3a89768731ee0d2f13dd8077c789b70e81a059323ae35ea970
- 入职时间：2016-10-14
- 所在单位：信息学院
- 学历：博士研究生毕业
- 办公地点：厦门市思明区曾厝垵西路厦门大学海韵园行政楼B404
- 性别：男
- 联系方式：13400742847
- 学位：哲学博士学位
- 在职信息：在职
- 毕业院校：浙江大学；法国索邦大学
- 2018年度福建省科技进步奖一等奖：城市交通多源感知与智能计算的研究和推广（排序第9）
- ACM UbiComp 2015, 2016 两次最佳论文提名奖（一作，国内高校首次）
访问量：
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[31]陈龙彪.PANDA: predicting road risks after natural disasters leveraging heterogeneous urban data.CCF Transactions on Pervasive Computing and Interaction,
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[32]陈龙彪.Spatio-temporal analysis of urban crime leveraging multisource crowdsensed data.PERSONAL AND UBIQUITOUS COMPUTING,2020,
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[33]陈龙彪.ESCORT: Fine-Grained Urban Crime Risk Inference Leveraging Heterogeneous Open Data.IEEE SYSTEMS JOURNAL,2020,15(3):4656-4667.
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[34]陈龙彪,Fog radio access network optimization for 5G leveraging user mobility and traffic data.Journal of Network and Computer Applications,2021,191
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[35]陈龙彪,王程,UVLens: Urban Village Boundary Identification and Population Estimation Leveraging Open Government Data.Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies,2020,5(2):
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[36]陈龙彪.Indoor 3D Human Trajectory Reconstruction Using Surveillance Camera Videos and Point Clouds.IEEE Transactions on Circuits and Systems for Video Technology,32(4):2482-2495.
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[37]陈龙彪,Data-Driven C-RAN Optimization Exploiting Traffic and Mobility Dynamics of Mobile Users.IEEE Transactions on Mobile Computing,2021,20(5):1773-1788.
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[38]范晓亮,陈龙彪.DeepSTD: Mining Spatio-Temporal Disturbances of Multiple Context Factors for Citywide Traffic Flow Prediction.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2019,21(9):3744-3755.
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[39]杨晨晖,陈龙彪.The Progress of Human Pose Estimation: A Survey and Taxonomy of Models Applied in 2D Human Pose Estimation.IEEE Access,8133330-133348.
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[40]范晓亮,陈龙彪.Urban traffic flow prediction algorithm based on graph convolutional neural networks.Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science),2020,54(6):1147-1155.
