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副教授

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石程(硕导)

发布时间:2020-04-20来源: 作者:

石程

职称 副教授

电子邮件:chengc_s@163.com

研究方向:高分辨率遥感处理模式识别特征提取深度学习等

 

主要工作经历:

2019/12-至今   伟德bevictor中文版 副教授

2018/11-2019/10   伟德bevictor中文版 讲师

2016/9-2018/10   澳门大学 博士后

2014/3-2014/10 英国伯明翰大学 访问员工

2012/9-2016/6   西安电子科技大学 计算机应用技术 工学博士学位

2009/9-2012/6   西安电子科技大学 计算机应用技术 工学硕士学位

 

承担科研项目:

1. 国家自然科学基金项目, 61902313, 面向高光谱图像分类的小样本学习网络构建与优化, 2020/01-2022/12,主持.

2. 陕西省高校科协青年人才托举计划项目,小样本条件下的高光谱图像分类研究, 2021/01-2022/12,主持.

 

 

部分第一作者发表学术论文:

[1] C. Shi, Z. Lv, H. Shen, L. Fang and Z. You, "Improved Metric Learning With the CNN for Very-High-Resolution Remote Sensing Image Classification," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 631-644, 2021.

[2] C.  Shi, L. Fang, Z. Lv and H. Shen, "Improved Generative Adversarial Networks for VHR Remote Sensing Image Classification," in IEEE Geoscience and Remote Sensing Letters, doi: 10.1109/LGRS.2020.3025099, 2021.

[5] C. Shi and C. Pun, "Multiscale Superpixel-Based Hyperspectral Image Classification Using Recurrent Neural Networks With Stacked Autoencoders," in IEEE Transactions on Multimedia, vol. 22, no. 2, pp. 487-501, 2020.

[3] C. Shi, Z. Lv, X. Yang, P. Xu, I. Bibi, “Hierarchical Multi-View Semi-Supervised Learning for Very High-Resolution Remote Sensing Image Classification”, in Remote Sensing, vol. 12, np. 6, pp. 1012, 2020.

[4] C. Shi, L. Fang and H. Shen, "Convolutional Neural Networks With Class-Driven Loss for Multiscale VHR Remote Sensing Image Classification," in IEEE Access, vol. 8, pp. 149162-149175, 2020.

[6] C.  Shi, J. Zhang, Z. You , et al. “3D Convolutional Neural Networks with Image Fusion for Hyperspectral Image Classification,” The 10th International Conference on Computer Engineering and Networks, 2020.

[7 ]C. Shi, C. Pun, “Adaptive multi-scale deep neural networks with perceptual loss for panchromatic and multispectral images classification,” Information Sciences, 2019, 490:1-17.

[9] C, Shi, C, Pun, “Superpixel-based 3D deep neural networks for hyperspectral image classification”, Pattern Recognition, vol. 74, pp. 600-616, 2018.

[8] C. Shi, C. Pun, “Multi-scale hierarchical recurrent neural networks for hyperspectral image classification”, Neurocomputing, vol. 74, pp. 600-616, 2018.

[10]C. Shi, C. Pun, “Perceptual Loss for Superpixel-Level Multispectral and Panchromatic Image Classification, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018: 1588-1592.

[11] C. Shi, F. Liu, L. Li, L. Jiao H. Hao, “Pan-sharpening via compressed superresolution reconstruction and multidictionary learning”, Journal of Applied Remote Sensing, vol. 12, pp. 016011, 2018.

[12] C. Shi, C. Pun, “3D Multi-resolution wavelet convolutional neural networks for hyperspectral image classification”, Information Science, vol. 420, pp. 49-65, 2017.

[13] C. Shi , F. Liu, L. Li, L. Jiao, Y. Duan,  “Learning interpolation via regional map for pan-sharpening”, IEEE Transactions on Geoscience and Remote Sensing, vol.53, no.6, pp. 3417-3431, 2015.