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Chengbin Wu
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2020 – today
- 2024
- [j10]Chengbin Wu, Yaohuan Huang, Haijun Yang, Ling Yao, Yesen Liu, Zhuo Chen:
An unmanned aerial system benchmark object detection dataset for deep learning in outfall surveys. Int. J. Digit. Earth 17(1) (2024) - [j9]Biao Xiong, Yaohuan Huang, Mingxing Chen, Chengbin Wu, Hongyan Ren:
An Annual "Urban Core-Suburban-Rural" Triad Structure Dataset for China From 1992 to 2021. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 17: 2037-2051 (2024) - 2023
- [j8]Yaohuan Huang, Chengbin Wu:
Evaluation of Deep Learning Benchmarks in Retrieving Outfalls Into Rivers With UAS Images. IEEE Trans. Geosci. Remote. Sens. 61: 1-12 (2023) - [j7]Yaohuan Huang, Chengbin Wu:
Erratum to "Evaluation of Deep Learning Benchmarks in Retrieving Outfalls Into Rivers With UAS Images". IEEE Trans. Geosci. Remote. Sens. 61: 1 (2023) - 2022
- [j6]Lianwei Li, Cunjin Xue, Yangfeng Xu, Chengbin Wu, Chaoran Niu:
PoSDMS: A Mining System for Oceanic Dynamics with Time Series of Raster-Formatted Datasets. Remote. Sens. 14(13): 2991 (2022) - [j5]Yaohuan Huang, Jie Yang, Mingxing Chen, Chengbin Wu, Hongyan Ren, Yesen Liu:
An Approach for Retrieving Consistent Time Series "Urban Core-Suburban-Rural" (USR) Structure Using Nighttime Light Data from DMSP/OLS and NPP/VIIRS. Remote. Sens. 14(15): 3642 (2022) - [j4]Yaohuan Huang, Chengbin Wu, Haijun Yang, Haitao Zhu, Mingxing Chen, Jie Yang:
An Improved Deep Learning Approach for Retrieving Outfalls Into Rivers From UAS Imagery. IEEE Trans. Geosci. Remote. Sens. 60: 1-14 (2022) - 2020
- [j3]Yaohuan Huang, Chengbin Wu, Mingxing Chen, Jie Yang, Hongyan Ren:
A Quantile Approach for Retrieving the "Core Urban-Suburban-Rural" (USR) Structure Based on Nighttime Light. Remote. Sens. 12(24): 4179 (2020)
2010 – 2019
- 2019
- [j2]Jingyi Liu, Cunjin Xue, Qing Dong, Chengbin Wu, Yangfeng Xu:
A Process-Oriented Spatiotemporal Clustering Method for Complex Trajectories of Dynamic Geographic Phenomena. IEEE Access 7: 155951-155964 (2019) - [j1]Cunjin Xue, Chengbin Wu, Jingyi Liu, Fenzhen Su:
A Novel Process-Oriented Graph Storage for Dynamic Geographic Phenomena. ISPRS Int. J. Geo Inf. 8(2): 100 (2019)
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