赵玥

2020-04-16

赵玥

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职称: 副教授

学科: 林业电气化与自动化

联系电话: +86-10-62337736

Email: zhaoyue0609@126.com


教育背景

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2005.09-2009.06 哈尔滨工程大学,测控技术与仪器专业(本科)
2009.09-2014.11
上海交通大学,控制理论与工程(硕博连读)


成就及获奖经历

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上海市科技进步三等奖(排名第三)

梁希林业科学技术二等奖(排名第三)


主要成果

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  1. Han, Q., Zhao, Y., Liu, L., Chen, Y. and Zhao, Y.*, 2019. A Simplified Convolutional Network for Soil Pore Identification Based on Computed Tomography Imagery. Soil Science Society of America Journal, 83(5): 1309-1318. (SCI, 2, TOP, IF:2.405)

  2. Han, Q., Liu, L., Zhao, Y.*, Zhao, Y.*, 2020. Ecological Big Data Adaptive Compression Method Combining 1D Convolutional Neural Network and Switching Idea. IEEE Access, 8: 20270-20278. (SCI, 2, IF:4.098)

  3. Han, Q., Zhou, X., Liu, L., Zhao, Y. and Zhao, Y.*, 2018. Three-dimensional visualization of soil pore structure using computed tomography. Journal of Forestry Research, 30(3): 1053-1061. (SCI, 3, IF:1.247)

  4. Zhao, Y., Han, Q., Zhao, Y. and Liu, J.*, 2018. Soil pore identification with the adaptive fuzzy C-means method based on computed tomography images. Journal of Forestry Research, 30(3): 1043-1052. (SCI, 3, IF:1.247)

  5. Zhao, Y. and Su, J.*, 2014. Local sharpness distribution–based feature points matching algorithm. Journal of Electronic Imaging, 23(1): 013011. (SCI,4,IF:0.924)

  6. Zhao, Y. and Su, J.*, 2015. New Sparse Facial Feature Description Model Based on Salience Evaluation of Regions and Features. International Journal of Pattern Recognition and Artificial Intelligence, 29(05): 1556007.1-1556007.21. (SCI,4,IF:1.110)

  7. Zhao, Y. and Su, J.*, 2014. Sparse learning for salient facial feature description. 2014 IEEE International Conference on Robotics and Automation (ICRA),. (EI 收录, 机器人领域国际顶级会议)

  8. Han, Q., Su, J. and Zhao, Y.*, 2019. More Adaptive and Updatable: An Online Sparse Learning Method for Face Recognition. Journal of Electrical and Computer Engineering, 2019, 1-7. (EI收录)

  9. 韩巧玲,赵玥*,赵燕东,刘克雄,庞曼.基于全卷积网络的土壤断层扫描图像中孔隙分割[J].农业工程学报,2019,35(02):128-133. (EI收录)

  10. 韩巧玲,赵玥,赵燕东,潘贤君,彭涌,郑一力*.基于细化法的土壤孔隙骨架提取算法研究[J].农业机械学报,2019,50(09):229-234. (EI收录)

  11. 赵玥,韩巧玲,赵燕东*.基于灰度-梯度特征的改进FCM土壤孔隙辨识方法[J].农业机械学报,2018,49(03):279-286. (EI收录)

  12. 赵玥,刘雷,韩巧玲,赵燕东*. 基于CT图像的土壤孔隙结构重构[J].农业机械学报, 2018, 49(S1): 401-406. (EI收录)

  13. 赵玥,谢辉平,高超,赵燕东*. 基于K-SVD基的林区监测站数据采集方法研究[J].农业机械学报, 2018, 49(S1): 365-371. (EI收录)

赵玥,韩巧玲,赵燕东*. 基于CT扫描技术的土壤孔隙定量表达优化[J].农业机械学报,2017,48(10):252-259. (EI收录)