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赵林，湖南湘潭人，博士，副教授，硕士生导师。2007年毕业于华中科技大学计算机学院获硕士学位，2017年毕业于中南大学welcome欢迎光临威尼斯获博士学位。现为湖南理工学院专职教师，信息与通信工程专业学术型硕士生导师、电子信息和机械（计算机视觉领域）专业型硕士生导师，主要从事人工智能、深度学习、计算机视觉以及智能控制等领域的研究工作。指导本科生、研究生获得数学建模竞赛国家一等奖1项、国家二等奖12项、省级一等奖6项、省级二、三等奖近10项；指导本科生获得“互联网+”大学生创新创业大赛湖南省二等奖1项，指导研究生获得电子竞赛华中地区三等奖1项；指导湖南省大学生研究性学习和创新性实验计划项目1项，湖南省研究生科研创新项目4项。现为湖南理工学院“机器视觉与人工智能研究中心”的核心研究成员，“Fox++（湖理智能）实验室负责人。在国内外重要期刊和国际会议发表论文30余篇，其中SCI/EI收录20多篇，获得法国巴黎举办的第9届IFAC工艺过程故障检测、监控和安全专题讨论会（the 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes）最佳论文提名奖，并兼任多个国际期刊审稿人。已获得授权国家发明专利5项。

1. 研究方向：

2. 计算机视觉

3. 人工智能算法

4. 智能控制

5. 主持或参加的科研项目：

   先后主持湖南省自然科学基金、湖南省教育厅科研重点项目、优秀青年项目、湖南省教育厅教改多个项目，参与国家级自然科学基金项目5项。主持研发横向项目多项，有丰富的图像信息处理领域项目开发经验。

6. 教学：

   《机器人及其控制》

   《自动控制工程案例》

   《数字图像处理》

7. 部分代表性论文:

8. Zhao L, Feng Y, Dai Y J, Wu J H*, Zhang G Y*. Progressive Contrastive Learning Based On Noisy Negatives Cleaning for Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Letters, 2024, DOI: 10.1109/LGRS.2024.3373628.

9. Fang C H, Zhang G F, Li J, Li X P, Chen T F, Zhao L*. Intelligent Agent for Hyperspectral Image Classification with Noisy Labels: A Deep Reinforcement Learning Framework[J]. International Journal of Remote Sensing, 2024.

10. Ouyang E, Li B, Hu W, Zhang G, Zhao L(通信作者), Wu J. When Multi-Granularity Meets Spatial-Spectral Attention: A Hybrid Transformer for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing, 2023, https://doi.org/10.1109/TGRS. 2023.3242978 (中科院 SCI一区)

11. Zhao L, Ouyang E, Tang J, Li B, Wu J, Zhang G. Domain transfer and difference-aware band weighting for object tracking in hyperspectral videos. International Journal of Remote Sensing, 2023, 44(4): 1115-1131, DOI: 10.1080/01431161.2023.2173034 (中科院SCI三区)

12. Zhao L, Tang L, Greene M S, Sa Y, Wang W, Jin J, ... Hu X. Deep Learning of Morphologic Correlations to Accurately Classify CD4+ and CD8+ T Cells by Diffraction Imaging Flow Cytometry. Analytical Chemistry, 2022, 94(3), 1567–1574 (中科院SCI一区)

13. Zhao L, Luo W, Liao Q, Chen S, Wu J. Hyperspectral Image Classification with Contrastive Self-Supervised Learning Under Limited Labeled Samples. IEEE Geoscience and Remote Sensing Letters, 2022, 19:1-5, Art no.6008205 (中科院SCI二区, ESI高被引)

14. Ouyang E, Wu J, Li B, Zhao L(通信作者), Hu W. Band Regrouping and Response-Level Fusion for End-to-End Hyperspectral Object Tracking. IEEE Geoscience and Remote Sensing Letters, 2022, 19: 1-5, Art no.6005805 (中科院SCI二区)

15. Wu J, He C, He J, Xie Y, Zhao L(通信作者), Zhang G. FSNet: A network for smoke image segmentation based on frequency characteristics. Control Theory & Applications, 2022 (EI)

(吴健辉,何灿,何俊康,谢永芳,赵林,张国云. FSNet:基于频率特性的烟雾图像分割网络. 控制理论与应用, 2022, http://kns.cnki.net/kcms/detail/44.1240.tp.20220701.1603.056.html)

1. Li B, Ouyang E, Hu W, Zhang G, Zhao L(通信作者), Wu J. Multi-granularity Vision Transformer Via Semantic token for Hyperspectral Image Classification. International Journal of Remote Sensing, 2022, 43(17): 6538-6560 (中科院SCI三区)

2. Zhao L, Li X, et al. Prediction method of gasoline octane number based on adaptive variable Weighting. Control and Decision, 2022, 37(10):2738-2744 (EI)

(赵林,李希,谢永芳,易嘉闻,吴健辉,胡文静. 基于自适应变量加权的汽油辛烷值预测方法. 控制与决策, 2022, 37(10): 2738-2744)

1. Liu L, Zhou X, Liao Q, Liao Q, Hu W, Zhao L(通信作者). Burst bubble recognition based on depth feature. In Proceedings of the 4th International Conference on Informatics Engineering & Information Science(ICIEIS2021), 12161:10-14, 2022 (EI)

2. Zhao L, Yi J, Li X, Hu W, Wu J, Zhang G. Compact band weighting module based on attention-driven for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, 2021, 59(11): 9540-9552 (中科院SCI二区)

3. Qin Y, Tian P, Zhao L, Mutisya S, Jin J, Lu J, Hu X. Robustness of inverse solutions for radiative transfer parameters from light signals measured with different detection configurations. Journal of Quantitative Spectroscopy and Radiative Transfer, 2021, 274: 107883 (中科院SCI二区)

4. Tian P, Qin Y, Zhao L, Mutisya S, Jin J, Lu J, Hu X. Multiparameter spectrophotometry platform for turbid sample measurement by robust solutions of radiative transfer problems. IEEE Transactions on Instrumentation and Measurement, 2020, 70: 1-10 (中科院SCI二区)

5. Wang W, Wen Y, Lu J, Zhao L, Safaa A, Hu X. Rapid classification of micron-sized particles of sphere, cylinders and ellipsoids by diffraction image parameters combined with scattered light intensity. Journal of Quantitative Spectroscopy and Radiative Transfer, 2019, 224: 453-459. (中科院SCI二区)

6. Zhao L, Peng T, Xie Y, Yang C, Gui W, Zhao Y. Froth stereo visual feature extraction for the industrial flotation Process. Industrial & Engineering Chemistry Research, 2019, 58(31): 14510-14519 (中科院SCI二区)

7. Tu B, Kuang W, Shang Y, He D, Zhao L. A multi-view object tracking using triplet model. Journal of Visual Communication and Image Representation, 2019, 60: 64-68 (中科院SCI三区)

8. Zhao L, Peng T, Xie Y, Yang C, Gui W. Recognition of flooding and sinking conditions in flotation process using soft measurement of froth surface level and QTA. Chemometrics and Intelligent Laboratory Systems, 2017, 169: 45-52 (中科院SCI三区)

9. Zhao L, Peng T, Zhao Y, Peng X, Xie Y. Features Extraction of flotation froth based on equivalent binocular stereo vision. IFAC-PapersOnLine, 2016, 49(20): 90-95 (EI)

10. Zhao L, Peng T, Zhao L, Peng X, Zhao Y, Song Y. Fault condition recognition based on multi-scale texture features and embedding prior knowledge k-means for antimony flotation process. IFAC-PapersOnLine, 2015, 48(21): 864-870 (EI)

11. Peng X, Peng T, Zhao L, Song Y, Gui W. Working condition recognition based on an improved NGLDM and interval data-based classifier for the antimony roughing process. Minerals Engineering, 2016, 86: 1-9 (中科院SCI二区)

12. Zou Y, Yang C, Wang X, Zhao L, Xie Y. Reagent Feed Intelligent Setting Based on Belief Rule Base for Antimony Roughing Flotation. In Proceedings of the 28th Chinese Control and Decision Conference (CCDC), pages 28-30, 2016 (EI)

(邹玉龙, 阳春华, 王晓丽, 赵林, 谢永芳. 基于置信规则库的锑粗选加药智能设定[C]//. 第28届中国控制与决策会议. 2014:638-642)

1. Zhao L, Peng T, Song Y, Li K, Wang Y. Association Recognition based on Rules for the Performance of Copper Flotation Process. In Proceedings of the 25th Chinese Process Control Conference, pages 638-642, 2014 (EI)

(赵林, 彭涛, 宋彦坡, 李康, 王艺霖. 基于规则的铝浮选工况关联识别[C]//. 第25届中国过程控制会议. 2014:638-642)

1. Li W, Li X, Zhao L. a Decision Support System for Books Procurement of University Libraries. In Proceedings of the 26th Chinese Control Conference, pages 3491-3494, 2007

(李武,李霞,赵林. 大学图书馆文献采访决策支持系统[C]//.第二十六届中国控制会议, 2007: 3491-3494) (EI)

1. 部分毕业学生情况：

1. 课题组招生：

2. 我们希望入学后的你

   （1）扎实的算法功底

   学会如何找到学术前沿，如何发现科学问题并寻找解决方案，如何设计算法并编程实现，如何开展算法评估测试与迭代改进；

   （2）良好的表达能力

   学会如何写一篇逻辑严密、论证充分、表达清晰的学术论文；学会如何做一个优雅得体、引人入胜的学术报告；

   （3）开放的个人胸怀

   学会与团队的良好协作，与全国智力精英的思维碰撞与交流，与企业和学术界的交流与合作；掌握持续自我学习的能力。

3. 我们期待毕业后的你

   （1）进入国内一流企业从事前沿技术研发；

   （2）在国内一流高校甚至海外知名高校读博深造；

   （3）开展高科技领域创新创业。

4. 联系方式：

   地址：湖南理工学院19栋305室

   邮编：414006

   Email：zhaol@hnist.edu.cn

   2023招新咨询QQ群：685967353