教授
入职时间:2011-10-28
所在单位:地球科学与信息物理学院
学历:博士研究生毕业
性别:男
学位:博士学位
在职信息:在职
毕业院校:中南大学
学科:测绘科学与技术
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最后更新时间:..
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[1]Jingru Zhu; Ya Guo; Geng Sun; Libo Yang; Min Deng; Jie Chen*; Unsupervised domain adaptation semantic segmentation of high-resolution remote sensing imagery with invariant domain-level prototype memory.IEEE Transactions on Geoscience and Remote Sensing, 2023, DOI: 10.1109/TGRS.2023.3243042
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[2]杨彬,毛银,陈晋,刘建强,陈杰,闫凯. 深度学习的遥感变化检测综述:文献计量与分析.遥感学报,XX(XX): 1-18 DOI: 10.11834/jrs.20222156.
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[3]Qin D D,Wan L,He P E,Zhang Y,Guo Y and Chen J*. 2022. Multiscale object detection in remote sensing image by combining data fusion and feature selection. National Remote Sensing Bulletin, 26(8):1662-1673 DOI: 10.11834/jrs.20221249.
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[4]Gang Xu; Yongjun Fang; Min Deng; Geng Sun; Jie Chen*. Remote Sensing Mapping of Build-Up Land with Noisy Label via Fault-Tolerant Learning.Remote Sensing, 2022, DOI: 10.3390/rs14092263
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[5]Gang Xu; Min Deng; Geng Sun; Ya Guo; Jie Chen*. Improving Building Extraction by Using Knowledge Distillation to Reduce the Impact of Label Noise.Remote Sensing, 2022, DOI: 10.3390/rs14225645
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[6]Jie Chen; Dengda Qin; et al. Multiscale Object Contrastive Learning-Derived Few-Shot Object Detection in VHR Imagery.IEEE Transactions on Geoscience and Remote Sensing, 2022, DOI: 10.1109/TGRS.2022.3229041
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[7]Jie Chen; Ya Guo; et al. Improving Few-Shot Remote Sensing Scene Classification With Class Name Semantics.IEEE Transactions on Geoscience and Remote Sensing. 2022. DOI: 10.1109/TGRS.2022.3219726
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[8]Jie Chen, Jingru Zhu.Unsupervised Domain Adaptation for Semantic Segmentation of High-Resolution Remote Sensing Imagery Driven by Category-Certainty Attention.IEEE Transactions on Geoscience and Remote Sensing, 2022, 60
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[9]Wafaa Majeed Mutashar Al-Hameedi, Jie Chen*, et al., Remote Sensing-Based Urban Sprawl Modeling Using Multilayer Perceptron Neural Network Markov Chain in Baghdad, Iraq.Remote Sensing, 2021
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[10]Zhang Y, Deng M, He F, Guo Y, Sun G, Chen J*, FODA: Building Change Detection in High-Resolution Remote Sensing Images based on Feature–Output Space Dual-Alignment.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021: [DOI: 10.1109/JSTARS.2021.3103429].
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[11]Chen J, Wang H, Guo Y, et al. Strengthen the Feature Distinguishability of Geo-Object Details in the Semantic Segmentation of High-Resolution Remote Sensing Images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 2327-2340.[DOI: 10.1109/JSTARS.2021.3053067]
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[12]Chen J, Huang H, Peng J, et al. Contextual Information-Preserved Architecture Learning for Remote-Sensing Scene Classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2021.[DOI: 10.1109/TGRS.2021.3063287]
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[13]Chen J, Zhou X, Zhang Y, et al. Message-Passing-Driven Triplet Representation for Geo-Object Relational Inference in HRSI[J]. IEEE Geoscience and Remote Sensing Letters, 2021.[DOI: 10.1109/LGRS.2020.3038569]
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[14]陈杰,戴欣宜,周兴,孙庚,邓敏.2021.双LSTM驱动的高分遥感影像地物目标空间关系语义描述.遥感学报,25(5):1085-1094.[DOI:10.11834/jrs.20210340]
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[15]Chen J, Yuan Z, Peng J, et al. DASNet: Dual attentive fully convolutional siamese networks for change detection of high resolution satellite images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 1194-1205.[DOI:10.1109/JSTARS.2020.3037893]
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[16]Chen J, Zhu J, Sun G, et al. SMAF-Net: Sharing Multiscale Adversarial Feature for High-Resolution Remote Sensing Imagery Semantic Segmentation[J]. IEEE Geoscience and Remote Sensing Letters, 2020.[DOI: 10.1109/LGRS.2020.3011151]
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[17]Chen J, Wan L, Zhu J, et al. Multi-scale spatial and channel-wise attention for improving object detection in remote sensing imagery[J]. IEEE Geoscience and Remote Sensing Letters, 2019, 17(4): 681-685.[DOI:10.1109/LGRS.2019.2930462]
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[18]Chen J, Han Y, Wan L, et al. Geospatial relation captioning for high-spatial-resolution images by using an attention-based neural network[J]. International Journal of Remote Sensing, 2019, 40(16): 6482-6498.[DOI:10.1080/01431161.2019.1594439]
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[19]Liu H, Yang M, Chen J, et al. Line-constrained shape feature for building change detection in VHR remote sensing imagery[J]. ISPRS International Journal of Geo-Information, 2018, 7(10): 410.[DOI:10.3390/ijgi7100410]
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[20]Chen J, Liu H, Hou J, et al. Improving Building Change Detection in VHR Remote Sensing Imagery by Combining Coarse Location and Co-Segmentation[J]. ISPRS International Journal of Geo-Information, 2018, 7(6): 213.[DOI:10.3390/ijgi7060213]